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Research in Education

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• Description
• Aims and Scope
• Editorial Board
• Abstracting / Indexing
• Submission Guidelines
• Clarivate Analytics: Emerging Sources Citation Index (ESCI)

Please read the guidelines below then visit the Journal’s submission site https://mc.manuscriptcentral.com/rie  to upload your manuscript. Please note that manuscripts not conforming to these guidelines may be returned.

Only manuscripts of sufficient quality that meet the aims and scope of Research in Education will be reviewed.

There are no fees payable to submit or publish in this Journal. Open Access options are available - see section 3.3 below.

As part of the submission process you will be required to warrant that you are submitting your original work, that you have the rights in the work, and that you have obtained and can supply all necessary permissions for the reproduction of any copyright works not owned by you, that you are submitting the work for first publication in the Journal and that it is not being considered for publication elsewhere and has not already been published elsewhere. Please see our guidelines on prior publication and note that Research in Education  may accept submissions of papers that have been posted on pre-print servers ; please alert the Editorial Office when submitting (contact details are at the end of these guidelines) and include the DOI for the preprint in the designated field in the manuscript submission system. Authors should not post an updated version of their paper on the preprint server while it is being peer reviewed for possible publication in the journal. If the article is accepted for publication, the author may re-use their work according to the journal's author archiving policy.

If your paper is accepted, you must include a link on your preprint to the final version of your paper.

• What do we publish? 1.1 Aims & Scope 1.2 Article types 1.3 Writing your paper
• Editorial policies 2.1 Peer review policy 2.2 Authorship 2.3 Acknowledgements 2.4 Funding 2.5 Declaration of conflicting interests 2.6 Research data
• Publishing policies 3.1 Publication ethics 3.2 Contributor's publishing agreement 3.3 Open access and author archiving
• Preparing your manuscript 4.1 Formatting 4.2 Artwork, figures and other graphics 4.3 Supplemental material 4.4 Reference style 4.5 English language editing services
• Submitting your manuscript 5.1 ORCID 5.2 Information required for completing your submission 5.3 Permissions
• On acceptance and publication 6.1 Sage Production 6.2 Online First publication 6.3 Access to your published article 6.4 Promoting your article
• Further information

1. What do we publish?

1.1 Aims & Scope

Before submitting your manuscript to Research in Education , please ensure you have read the  Aims & Scope

1.2 Article Types

Research in Education  accepts the following (all will undergo peer review; may be solicited or unsolicited):

Full papers: up to 7000 words

• Theoretically innovative contributions to ongoing debates in Education.

Research notes: 3000 - 4000 words

Short, concise reports and discussions, from a particular investigation/study that focus on:

• Significant emergent findings
• Conceptual, practical or methodological innovations, or
• Points of departure for future studies.

Reviews/Essays (4000 – 5000 words)

• These will describe new developments of broad significance in education, with a focus on identifying unresolved questions and future research directions.
• Should aim to convey new developments in a field and its implications, whether theoretical, empirical, or methodological.
• Should include an abstract, an introduction that outlines the main point, brief subheadings, and up to 40 references

Review papers (graduate student): up to 5000 words

• Critically analytic syntheses of relevant literature in areas covered by the journal, demonstrating high quality student scholarship.
• Authors must be a student, i.e. not yet holding a doctoral qualification, at the time of publication, and papers must be identified as a 'Review paper (graduate student)' on first submission

Two distinctive features of Research in Education :

• The Critical Exchange involves two invited authors each of whom is asked to write 4,000 words in response to a prompt. The two authors then read each other's initial contribution and respond with a further 1,000 words. We hope to thus generate vibrant and constructive scholarly debate on issues of interest and significance to our readers.
• Papers in response to a book or paper: involves two or three authors each of whom is asked write 1500 – 2000 words that articulate personal viewpoints or learning, or review key themes, as they relate specifically to a book or paper that is relevant to the areas covered by the journal.  Works are identified by the Editors, and original authors are invited to respond to the submitted papers.  Submissions are via a Call for Papers, or Editorial invitation.

Special issues are welcome: may be solicited or unsolicited, result from a Call for Papers, be generated by papers produced by a project or a conference, or in response to invitation to expert/keynote authorship by the Editors.

Each year an award of Best Review Paper (graduate student) will be decided by a sub-committee of the Editorial Board.  The winner will receive a Sage book voucher with the winning paper featured on the journal homepage. The prize will recognise the winning article published in an issue in the previous year. The sub-committee’s decision will be based on the quality of:

• the writing, structure and analytical synthesis presented, and
• contribution to the understanding of a particular topic,  or to broader theoretical, conceptual or methodological issues in Education.

1.3 Writing your paper

The Sage Author Gateway has some general advice and on  how to get published , plus links to further resources. Sage Author Services also offers authors a variety of ways to improve and enhance their article including English language editing, plagiarism detection, and video abstract and infographic preparation.

1.3.1 Make your article discoverable

For information and guidance on how to make your article more discoverable, visit our Gateway page on How to Help Readers Find Your Article Online .

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2. Editorial policies

2.1 Peer review policy

Research in Education  adheres to a rigorous double-blind reviewing policy in which the identity of both the reviewer and author are always concealed from both parties.

2.2 Authorship

All parties who have made a substantive contribution to the article should be listed as authors. Principal authorship, authorship order, and other publication credits should be based on the relative scientific or professional contributions of the individuals involved, regardless of their status. A student is usually listed as principal author on any multiple-authored publication that substantially derives from the student’s dissertation or thesis.

         Please note that AI chatbots, for example ChatGPT, should not be listed as authors. For more information see the policy on Use of ChatGPT and generative AI tools .

2.3 Acknowledgements

All contributors who do not meet the criteria for authorship should be listed in an Acknowledgements section. Examples of those who might be acknowledged include a person who provided purely technical help, or a department chair who provided only general support.

Please supply any personal acknowledgements separately to the main text to facilitate anonymous peer review.

2.3.1 Third party submissions

Where an individual who is not listed as an author submits a manuscript on behalf of the author(s), a statement must be included in the Acknowledgements section of the manuscript and in the accompanying cover letter. The statements must:

• Disclose this type of editorial assistance – including the individual’s name, company and level of input
• Identify any entities that paid for this assistance
• Confirm that the listed authors have authorized the submission of their manuscript via third party and approved any statements or declarations, e.g. conflicting interests, funding, etc.

Where appropriate, Sage reserves the right to deny consideration to manuscripts submitted by a third party rather than by the authors themselves .

2.3.2 Writing assistance

Individuals who provided writing assistance, e.g. from a specialist communications company, do not qualify as authors and so should be included in the Acknowledgements section. Authors must disclose any writing assistance – including the individual’s name, company and level of input – and identify the entity that paid for this assistance”).

It is not necessary to disclose use of language polishing services.

2.4 Funding

Research in Education requires all authors to acknowledge their funding in a consistent fashion under a separate heading.  Please visit the Funding Acknowledgements page on the Sage Journal Author Gateway to confirm the format of the acknowledgment text in the event of funding, or state that: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. 

2.5 Declaration of conflicting interests

Research in Education encourages authors to include a declaration of any conflicting interests and recommends you review the good practice guidelines on the Sage Journal Author Gateway .

2.6 Research data

The journal is committed to facilitating openness, transparency and reproducibility of research, and has the following research data sharing policy. For more information, including FAQs please visit the Sage Research Data policy pages .

Subject to appropriate ethical and legal considerations, authors are encouraged to:

• share your research data in a relevant public data repository
• include a data availability statement linking to your data. If it is not possible to share your data, we encourage you to consider using the statement to explain why it cannot be shared.
• cite this data in your research

3. Publishing Policies

3.1 Publication ethics

Sage is committed to upholding the integrity of the academic record. We encourage authors to refer to the Committee on Publication Ethics’ International Standards for Authors and view the Publication Ethics page on the Sage Author Gateway

3.1.1 Plagiarism

Research in Education and Sage take issues of copyright infringement, plagiarism or other breaches of best practice in publication very seriously. We seek to protect the rights of our authors and we always investigate claims of plagiarism or misuse of published articles. Equally, we seek to protect the reputation of the journal against malpractice. Submitted articles may be checked with duplication-checking software. Where an article, for example, is found to have plagiarised other work or included third-party copyright material without permission or with insufficient acknowledgement, or where the authorship of the article is contested, we reserve the right to take action including, but not limited to: publishing an erratum or corrigendum (correction); retracting the article; taking up the matter with the head of department or dean of the author's institution and/or relevant academic bodies or societies; or taking appropriate legal action.

3.1.2 Prior publication

If material has been previously published it is not generally acceptable for publication in a Sage journal. However, there are certain circumstances where previously published material can be considered for publication. Please refer to the guidance on the Sage Author Gateway or if in doubt, contact the Editor at the address given below.

3.2 Contributor's publishing agreement

Before publication, Sage requires the author as the rights holder to sign a Journal Contributor’s Publishing Agreement. Sage’s Journal Contributor’s Publishing Agreement is an exclusive licence agreement which means that the author retains copyright in the work but grants Sage the sole and exclusive right and licence to publish for the full legal term of copyright. Exceptions may exist where an assignment of copyright is required or preferred by a proprietor other than Sage. In this case copyright in the work will be assigned from the author to the society. For more information please visit the Sage Author Gateway .

3.3 Open access and author archiving

Research in Education offers optional open access publishing via the Sage Choice programme and Open Access agreements, where authors can publish open access either discounted or free of charge depending on the agreement with Sage. Find out if your institution is participating by visiting Open Access Agreements at Sage . For more information on Open Access publishing options at Sage please visit Sage Open Access . For information on funding body compliance, and depositing your article in repositories, please visit Sage’s Author Archiving and Re-Use Guidelines and Publishing Policies .

4. Preparing your manuscript for submission

4.1 Formatting

The preferred format for your manuscript is Word. LaTeX files are also accepted. Word and (La)Tex templates are available on the Manuscript Submission Guidelines page of our Author Gateway.

4.2 Artwork, figures and other graphics

For guidance on the preparation of illustrations, pictures and graphs in electronic format, please visit Sage’s Manuscript Submission Guidelines   

Figures supplied in colour will appear in colour online regardless of whether or not these illustrations are reproduced in colour in the printed version. For specifically requested colour reproduction in print, you will receive information regarding the costs from Sage after receipt of your accepted article.

4.3 Supplemental material

This journal is able to host additional materials online (e.g. datasets, podcasts, videos, images etc) alongside the full-text of the article. For more information please refer to our guidelines on submitting supplementary files

4.4 Reference style

Research in Education adheres to the Sage Harvard reference style. View the Sage Harvard guidelines to ensure your manuscript conforms to this reference style.

If you use EndNote to manage references, you can download the Sage Harvard EndNote output file

4.5 English language editing services

Authors seeking assistance with English language editing, translation, or figure and manuscript formatting to fit the journal’s specifications should consider using Sage Language Services. Visit Sage Language Services on our Journal Author Gateway for further information.

5. Submitting your manuscript

Research in Education is hosted on Sage Track, a web based online submission and peer review system powered by ScholarOne™ Manuscripts. Visit https://mc.manuscriptcentral.com/rie to login and submit your article online.

IMPORTANT: Please check whether you already have an account in the system before trying to create a new one. If you have reviewed or authored for the journal in the past year it is likely that you will have had an account created.  For further guidance on submitting your manuscript online please visit ScholarOne Online Help.

As part of our commitment to ensuring an ethical, transparent and fair peer review process Sage is a supporting member of ORCID, the Open Researcher and Contributor ID . ORCID provides a unique and persistent digital identifier that distinguishes researchers from every other researcher, even those who share the same name, and, through integration in key research workflows such as manuscript and grant submission, supports automated linkages between researchers and their professional activities, ensuring that their work is recognized.

The collection of ORCID IDs from corresponding authors is now part of the submission process of this journal. If you already have an ORCID ID you will be asked to associate that to your submission during the online submission process. We also strongly encourage all co-authors to link their ORCID ID to their accounts in our online peer review platforms. It takes seconds to do: click the link when prompted, sign into your ORCID account and our systems are automatically updated. Your ORCID ID will become part of your accepted publication’s metadata, making your work attributable to you and only you. Your ORCID ID is published with your article so that fellow researchers reading your work can link to your ORCID profile and from there link to your other publications.

If you do not already have an ORCID ID please follow this link  to create one or visit our ORCID homepage to learn more.

5.2 Information required for completing your submission

You will be asked to provide contact details and academic affiliations for all co-authors via the submission system and identify who is to be the corresponding author. These details must match what appears on your manuscript. The affiliation listed in the manuscript should be the institution where the research was conducted. If an author has moved to a new institution since completing the research, the new affiliation can be included in a manuscript note at the end of the paper. At this stage please ensure you have included all the required statements and declarations and uploaded any additional supplementary files (including reporting guidelines where relevant).

5.3 Permissions

Please also ensure that you have obtained any necessary permission from copyright holders for reproducing any illustrations, tables, figures or lengthy quotations previously published elsewhere. For further information including guidance on fair dealing for criticism and review, please see the Copyright and Permissions page on the Sage Author Gateway

6. On acceptance and publication

6.1 Sage Production

Your Sage Production Editor will keep you informed as to your article’s progress throughout the production process. Proofs will be made available to the corresponding author via our editing portal Sage Edit or by email, and corrections should be made directly or notified to us promptly. Authors are reminded to check their proofs carefully to confirm that all author information, including names, affiliations, sequence and contact details are correct, and that Funding and Conflict of Interest statements, if any, are accurate.

6.2 Online First publication

Online First allows final articles (completed and approved articles awaiting assignment to a future issue) to be published online prior to their inclusion in a journal issue, which significantly reduces the lead time between submission and publication. Visit the Sage Journals help page for more details, including how to cite Online First articles.

6.3 Access to your published article

Sage provides authors with online access to their final article.

6.4 Promoting your article

Publication is not the end of the process! You can help disseminate your paper and ensure it is as widely read and cited as possible. The Sage Author Gateway has numerous resources to help you promote your work. Visit the Promote Your Article page on the Gateway for tips and advice.

7. Further information

Any correspondence, queries or additional requests for information on the manuscript submission process should be sent to the Research in Education editorial office as follows:

Research in Education University of Aberdeen [email protected]

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In This Article Expand or collapse the "in this article" section Case Study in Education Research

Introduction, general overview and foundational texts of the late 20th century.

• Conceptualisations and Definitions of Case Study
• Case Study and Theoretical Grounding
• Choosing Cases
• Methodology, Method, Genre, or Approach
• Case Study: Quality and Generalizability
• Multiple Case Studies
• Exemplary Case Studies and Example Case Studies
• Criticism, Defense, and Debate around Case Study

Related Articles Expand or collapse the "related articles" section about

About related articles close popup.

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• Data Collection in Educational Research
• Mixed Methods Research
• Program Evaluation

Other Subject Areas

Forthcoming articles expand or collapse the "forthcoming articles" section.

• English as an International Language for Academic Publishing
• Girls' Education in the Developing World
• History of Education in Europe
• Find more forthcoming articles...
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Case Study in Education Research by Lorna Hamilton LAST REVIEWED: 27 June 2018 LAST MODIFIED: 27 June 2018 DOI: 10.1093/obo/9780199756810-0201

It is important to distinguish between case study as a teaching methodology and case study as an approach, genre, or method in educational research. The use of case study as teaching method highlights the ways in which the essential qualities of the case—richness of real-world data and lived experiences—can help learners gain insights into a different world and can bring learning to life. The use of case study in this way has been around for about a hundred years or more. Case study use in educational research, meanwhile, emerged particularly strongly in the 1970s and 1980s in the United Kingdom and the United States as a means of harnessing the richness and depth of understanding of individuals, groups, and institutions; their beliefs and perceptions; their interactions; and their challenges and issues. Writers, such as Lawrence Stenhouse, advocated the use of case study as a form that teacher-researchers could use as they focused on the richness and intensity of their own practices. In addition, academic writers and postgraduate students embraced case study as a means of providing structure and depth to educational projects. However, as educational research has developed, so has debate on the quality and usefulness of case study as well as the problems surrounding the lack of generalizability when dealing with single or even multiple cases. The question of how to define and support case study work has formed the basis for innumerable books and discursive articles, starting with Robert Yin’s original book on case study ( Yin 1984 , cited under General Overview and Foundational Texts of the Late 20th Century ) to the myriad authors who attempt to bring something new to the realm of case study in educational research in the 21st century.

This section briefly considers the ways in which case study research has developed over the last forty to fifty years in educational research usage and reflects on whether the field has finally come of age, respected by creators and consumers of research. Case study has its roots in anthropological studies in which a strong ethnographic approach to the study of peoples and culture encouraged researchers to identify and investigate key individuals and groups by trying to understand the lived world of such people from their points of view. Although ethnography has emphasized the role of researcher as immersive and engaged with the lived world of participants via participant observation, evolving approaches to case study in education has been about the richness and depth of understanding that can be gained through involvement in the case by drawing on diverse perspectives and diverse forms of data collection. Embracing case study as a means of entering these lived worlds in educational research projects, was encouraged in the 1970s and 1980s by researchers, such as Lawrence Stenhouse, who provided a helpful impetus for case study work in education ( Stenhouse 1980 ). Stenhouse wrestled with the use of case study as ethnography because ethnographers traditionally had been unfamiliar with the peoples they were investigating, whereas educational researchers often worked in situations that were inherently familiar. Stenhouse also emphasized the need for evidence of rigorous processes and decisions in order to encourage robust practice and accountability to the wider field by allowing others to judge the quality of work through transparency of processes. Yin 1984 , the first book focused wholly on case study in research, gave a brief and basic outline of case study and associated practices. Various authors followed this approach, striving to engage more deeply in the significance of case study in the social sciences. Key among these are Merriam 1988 and Stake 1995 , along with Yin 1984 , who established powerful groundings for case study work. Additionally, evidence of the increasing popularity of case study can be found in a broad range of generic research methods texts, but these often do not have much scope for the extensive discussion of case study found in case study–specific books. Yin’s books and numerous editions provide a developing or evolving notion of case study with more detailed accounts of the possible purposes of case study, followed by Merriam 1988 and Stake 1995 who wrestled with alternative ways of looking at purposes and the positioning of case study within potential disciplinary modes. The authors referenced in this section are often characterized as the foundational authors on this subject and may have published various editions of their work, cited elsewhere in this article, based on their shifting ideas or emphases.

Merriam, S. B. 1988. Case study research in education: A qualitative approach . San Francisco: Jossey-Bass.

This is Merriam’s initial text on case study and is eminently accessible. The author establishes and reinforces various key features of case study; demonstrates support for positioning the case within a subject domain, e.g., psychology, sociology, etc.; and further shapes the case according to its purpose or intent.

Stake, R. E. 1995. The art of case study research . Thousand Oaks, CA: SAGE.

Stake is a very readable author, accessible and yet engaging with complex topics. The author establishes his key forms of case study: intrinsic, instrumental, and collective. Stake brings the reader through the process of conceptualizing the case, carrying it out, and analyzing the data. The author uses authentic examples to help readers understand and appreciate the nuances of an interpretive approach to case study.

Stenhouse, L. 1980. The study of samples and the study of cases. British Educational Research Journal 6:1–6.

DOI: 10.1080/0141192800060101

A key article in which Stenhouse sets out his stand on case study work. Those interested in the evolution of case study use in educational research should consider this article and the insights given.

Yin, R. K. 1984. Case Study Research: Design and Methods . Beverley Hills, CA: SAGE.

This preliminary text from Yin was very basic. However, it may be of interest in comparison with later books because Yin shows the ways in which case study as an approach or method in research has evolved in relation to detailed discussions of purpose, as well as the practicalities of working through the research process.

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• About Education »
• Meet the Editorial Board »
• Academic Achievement
• Academic Audit for Universities
• Academic Freedom and Tenure in the United States
• Action Research in Education
• Adjuncts in Higher Education in the United States
• Administrator Preparation
• Adolescence
• Advanced Placement and International Baccalaureate Courses
• Advocacy and Activism in Early Childhood
• African American Racial Identity and Learning
• Alaska Native Education
• Alternative Certification Programs for Educators
• Alternative Schools
• American Indian Education
• Animals in Environmental Education
• Art Education
• Artificial Intelligence and Learning
• Assessing School Leader Effectiveness
• Assessment, Behavioral
• Assessment, Educational
• Assessment in Early Childhood Education
• Assistive Technology
• Augmented Reality in Education
• Beginning-Teacher Induction
• Bilingual Education and Bilingualism
• Black Undergraduate Women: Critical Race and Gender Perspe...
• Blended Learning
• Case Study in Education Research
• Changing Professional and Academic Identities
• Character Education
• Children’s and Young Adult Literature
• Children's Beliefs about Intelligence
• Children's Rights in Early Childhood Education
• Citizenship Education
• Civic and Social Engagement of Higher Education
• Classroom Learning Environments: Assessing and Investigati...
• Classroom Management
• Coherent Instructional Systems at the School and School Sy...
• College Admissions in the United States
• College Athletics in the United States
• Community Relations
• Comparative Education
• Computer-Assisted Language Learning
• Computer-Based Testing
• Conceptualizing, Measuring, and Evaluating Improvement Net...
• Continuous Improvement and "High Leverage" Educational Pro...
• Counseling in Schools
• Critical Approaches to Gender in Higher Education
• Critical Perspectives on Educational Innovation and Improv...
• Critical Race Theory
• Crossborder and Transnational Higher Education
• Cross-National Research on Continuous Improvement
• Cross-Sector Research on Continuous Learning and Improveme...
• Cultural Diversity in Early Childhood Education
• Culturally Responsive Leadership
• Culturally Responsive Pedagogies
• Culturally Responsive Teacher Education in the United Stat...
• Curriculum Design
• Data-driven Decision Making in the United States
• Deaf Education
• Desegregation and Integration
• Design Thinking and the Learning Sciences: Theoretical, Pr...
• Development, Moral
• Dialogic Pedagogy
• Digital Age Teacher, The
• Digital Citizenship
• Digital Divides
• Disabilities
• Distance Learning
• Distributed Leadership
• Doctoral Education and Training
• Early Childhood Education and Care (ECEC) in Denmark
• Early Childhood Education and Development in Mexico
• Early Childhood Education in Aotearoa New Zealand
• Early Childhood Education in Australia
• Early Childhood Education in China
• Early Childhood Education in Europe
• Early Childhood Education in Sub-Saharan Africa
• Early Childhood Education in Sweden
• Early Childhood Education Pedagogy
• Early Childhood Education Policy
• Early Childhood Education, The Arts in
• Early Childhood Mathematics
• Early Childhood Science
• Early Childhood Teacher Education
• Early Childhood Teachers in Aotearoa New Zealand
• Early Years Professionalism and Professionalization Polici...
• Economics of Education
• Education For Children with Autism
• Education for Sustainable Development
• Education Leadership, Empirical Perspectives in
• Education of Native Hawaiian Students
• Education Reform and School Change
• Educational Statistics for Longitudinal Research
• Educator Partnerships with Parents and Families with a Foc...
• Emotional and Affective Issues in Environmental and Sustai...
• Emotional and Behavioral Disorders
• Environmental and Science Education: Overlaps and Issues
• Environmental Education
• Environmental Education in Brazil
• Epistemic Beliefs
• Equity and Improvement: Engaging Communities in Educationa...
• Equity, Ethnicity, Diversity, and Excellence in Education
• Ethical Research with Young Children
• Ethics and Education
• Ethics of Teaching
• Ethnic Studies
• Evidence-Based Communication Assessment and Intervention
• Family and Community Partnerships in Education
• Family Day Care
• Federal Government Programs and Issues
• Feminization of Labor in Academia
• Finance, Education
• Financial Aid
• Formative Assessment
• Future-Focused Education
• Gender and Achievement
• Gender and Alternative Education
• Gender, Power and Politics in the Academy
• Gender-Based Violence on University Campuses
• Gifted Education
• Global Mindedness and Global Citizenship Education
• Global University Rankings
• Governance, Education
• Grounded Theory
• Growth of Effective Mental Health Services in Schools in t...
• Higher Education and Globalization
• Higher Education and the Developing World
• Higher Education Faculty Characteristics and Trends in the...
• Higher Education Finance
• Higher Education Governance
• Higher Education Graduate Outcomes and Destinations
• Higher Education in Africa
• Higher Education in China
• Higher Education in Latin America
• Higher Education in the United States, Historical Evolutio...
• Higher Education, International Issues in
• Higher Education Management
• Higher Education Policy
• Higher Education Research
• Higher Education Student Assessment
• High-stakes Testing
• History of Early Childhood Education in the United States
• History of Education in the United States
• History of Technology Integration in Education
• Homeschooling
• Inclusion in Early Childhood: Difference, Disability, and ...
• Inclusive Education
• Indigenous Education in a Global Context
• Indigenous Learning Environments
• Indigenous Students in Higher Education in the United Stat...
• Infant and Toddler Pedagogy
• Inservice Teacher Education
• Integrating Art across the Curriculum
• Intelligence
• Intensive Interventions for Children and Adolescents with ...
• International Perspectives on Academic Freedom
• Intersectionality and Education
• Knowledge Development in Early Childhood
• Leadership Development, Coaching and Feedback for
• Leadership in Early Childhood Education
• Leadership Training with an Emphasis on the United States
• Learning Analytics in Higher Education
• Learning Difficulties
• Learning, Lifelong
• Learning, Multimedia
• Learning Strategies
• Legal Matters and Education Law
• LGBT Youth in Schools
• Linguistic Diversity
• Linguistically Inclusive Pedagogy
• Literacy Development and Language Acquisition
• Literature Reviews
• Mathematics Identity
• Mathematics Instruction and Interventions for Students wit...
• Mathematics Teacher Education
• Measurement for Improvement in Education
• Measurement in Education in the United States
• Meta-Analysis and Research Synthesis in Education
• Methodological Approaches for Impact Evaluation in Educati...
• Methodologies for Conducting Education Research
• Mindfulness, Learning, and Education
• Motherscholars
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Classroom Q&A

With larry ferlazzo.

In this EdWeek blog, an experiment in knowledge-gathering, Ferlazzo will address readers’ questions on classroom management, ELL instruction, lesson planning, and other issues facing teachers. Send your questions to [email protected]. Read more from this blog.

What Are the Most Important Education Research Findings in the Past 10 Years?

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(This is the first post in a two-part series.)

The new question-of-the-week is:

What do you think have been the most important education research findings from the past 10 years, and what areas are you hoping researchers focus on in the next 10 years?

There is so much education research out there, and much of it is inaccessible to K-12 teachers either because it’s written in arcane academic language or because it’s locked behind paywalls.

This series will try to highlight some of the most important findings that we teachers—and our students—can use.

Today, Beth M. Miller, Ph.D., and Jana Echevarria, Ph.D., share their reflections.

You might also be interested in many curated resources on ed. research at “Best” Lists o f the Week: Education Research .

Two ‘Streams’

Beth M. Miller, Ph.D., serves as the chief knowledge officer at EL Education. She leads the research, communications, and publications teams while mostly being in complete awe of the mad skills of her brilliant, compassionate, committed colleagues:

What happens in the learning process? Why do some students thrive at school and learn more than others, and why does this variation often reflect socially constructed racial and ethnic categories? In the last 10 years, two streams of research have vastly expanded our understanding of the answers to these complex but never-more-important questions.

Stream One: Research on How Students Learn

We now know, with greater clarity and evidence than ever, that learning is a social, emotional, and cognitive process. While early “brain research” findings were beginning to emerge 10 years ago (e.g., plasticity of the brain), in the past decade, this knowledge has converged in a growing science of learning and development (SoLD) with many important implications for instructional practices, school climate, and district policy.

Social-emotional learning (SEL) is deeply connected to academic achievement. We are increasingly learning that SEL can be developed in schools and that an integrated educational approach that deeply intertwines strands of social-emotional and academic development (versus teaching character as a siloed class on Tuesday mornings, for example) will be most effective.

Another key concept that has been developed through a body of evidence is the idea of mindset—how the student thinks of themself in relation to an idea or content will mediate their learning process and achievement. This insight from psychology, first developed by Carol Dweck, has resulted in a whole field of social psychology. Some of the short-term interventions have what seem like astounding results, because shifts in student mindset create a domino effect on motivation, self-efficacy, behavior, performance, and achievement.

For example, in several studies by David Yeager and his colleagues , teacher responses on a homework assignment communicating high expectations—and a belief that a student could reach these expectations—resulted in striking shifts in student academic performance over the course of a year. Teacher mindset also matters: When teachers who were trained on brain plasticity as it related to mathematics shifted their approach to teaching accordingly, doing so resulted in higher student achievement.

Stream Two: Research on the Impact of Racism in Education

Science of learning and development research can help to shift the dynamics of student experience and outcomes, but it is not enough to reach the goal we must attain: equitable learning opportunities and outcomes for all students. Another stream of research, less developed but equally imperative, is helping to uncover the ways that racism and other forms of marginalization create roadblocks to learning for millions of students and have throughout our history.

We can see this in the unequal financing of education between communities, the differences in teacher quality and facilities, and in the school experiences of millions of students. Despite the existence of brilliant students in every classroom and community, only some students will get the opportunity to develop to their full potential. In the last decade, research has highlighted how racism operates at every level of our education systems and, therefore, how to change it.

This body of research, often rooted in the theoretical work of scholars such as Gloria Ladson-Billings’ cconcept of “culturally relevant pedagogy” that she developed in the 1990s, includes ethnographic studies, correlational research, and quantitative large-scale studies, building a powerful body of evidence that racism and other forms of marginalization deeply and powerfully affect student achievement. Flipping the deficit-focused narrative of the “achievement gap” on its head, these researchers examine the resource gaps, opportunity gaps, racism, bias, and other processes and structures that drive differential experiences in school.

What we’ve learned might be a surprise to white people like me, but it only serves to expose the truth of what many people of color have experienced throughout their educational journey: Racism is deeply embedded in schools—by design, albeit often without conscious intention. Schools are a microcosm of our larger society. Without deep-seated, ongoing changes at multiple levels to shift that reality, racism remains a potent driver of school experiences and outcomes.

From research on the disproportionality of disciplinary practices to the impact on Black students of having even one Black teacher , we see racism—and other forms of marginalization—showing up anywhere we bring a lens to this study. We’ve learned a lot about the ways in which education policies, systems, and structures embed racism over the past decade. But that doesn’t mean individual teachers are off the hook: Multiple studies demonstrate the presence of negative perceptions and lower expectations of Black students on the part of many white teachers.

While deeply embedded policies and unconscious bias aren’t easy to shift, we are seeing evidence that it is not only possible to change these destructive dynamics, but also that this work significantly impacts student growth and learning. For example, a carefully designed training aimed at increasing teachers’ empathy for their students’ perspective by Jason Okonofua and colleagues shifted teachers from responding to behavior issues with punitive disciplinary practice to greater understanding and connection, leading to a 50 percent reduction in disciplinary actions. Other promising approaches, many rooted in culturally responsive education, from a community-center mathematics curriculum to the impact of ethnic - studies programs .

Where Do We Go From Here?

For the next 10 years, the most important work in education—whether in research studies or classrooms—will be in expanding the knowledge base where these two streams converge, i.e., combining what we know about how people learn, grow, and change with research that foregrounds the experiences and outcomes of historically marginalized students. After decades of education reforms that had little or no impact on the “stubborn” inequities in education, we have finally begun large-scale efforts to shift from measuring gaps to understanding why they exist and how we—not students—are the key to changing the dynamics. Some researchers, as well as organizations such as CASEL and the National Equity Project , are making progress, but we are in the early stages of this work. One thing we do know is that individual, incremental change will not create the equitable education system that our students deserve: Systemic changes in districts and charter networks will be needed, and we are only beginning the journey of creating the conditions at scale for all students to thrive.

One last note: We need to build on the current research base that demonstrates how disrupting racism benefits all students, including white students who will grow up in a diverse society. All students need the opportunity to experience what Rudine Sims Bishop coined “windows” as well as “mirrors” and deeply understand the multitude of experiences, histories, and perspectives we share in this country and around the world. Evidence that this learning matters—for all students—will help us create classrooms that enable us to build a better world.

English-Language Learners

Jana Echevarria, Ph.D., is professor emerita at California State University, Long Beach, where she was selected as Outstanding Professor. She is the co-developer of the SIOP Model of instruction for English-learners and the co-author of Making Content Comprehensible for English Learners: The SIOP Model and 99 Ideas and Activities for Teaching English Learners among other publications. Her blog is found at janaechevarria.com :

There are innumerable books, articles, and blogs written about what works with English-learners (ELs), but these resources don’t always reflect research-validated approaches and interventions. Empirical studies provide guidance for achieving desired outcomes that go beyond what intuitively seems like a good idea for teaching students in this population. The following areas of research are of particular importance in informing practice, especially for EL students.

Academic language . Cummins (1979) introduced the distinction between conversational language and academic language, and others more recently have discussed specific ways that academic language is challenging ( Scheppegrell, 2020 ), particularly for English - learners . Academic language is more formal and abstract than conversational language and uses complex sentence structure (e.g., embedded clauses and conjunctions), highly sophisticated, abstract vocabulary (e.g., representational democracy in social studies), and rhetorical forms (e.g., figurative language), and it is encountered almost exclusively in school.

Research has identified the critical relationship of academic language to reading comprehension, a cognitive and linguistic process needed to acquire and use knowledge in every academic-content area. As EL students become more proficient in English, they become more efficient readers and more similar to their English-speaking peers in their reading ability. Conversely, if EL students don’t become sufficiently proficient in English, they expend more cognitive effort, and their reading remains inefficient, which negatively affects achievement and motivation.

The importance of advancing academic-language development is clear. Findings verify that ELs don’t “pick up” academic language nor will the achievement gap close without explicit instruction in English-language development (ELD). A separate ELD time each day focusing on English-language instruction is critical but may not be sufficient for expediting English-language growth. In every content lesson, teaching key content vocabulary and exploiting teachable academic language-learning opportunities likely will enhance English proficiency.

Student assets . The idea that students come to school as empty vessels in need of filling has been dispelled. Indeed, students begin school with a minimum of five years of lived experiences, accumulated knowledge, and language development in their home language, and these continue to grow with each subsequent year. This treasure trove should be acknowledged and built upon as students learn academic content in school.

For English-learners, some lived experiences are culturally influenced, such as attending quinceañeras or receiving red envelopes as gifts, and others are common to their age group such as popular social media sites, video games, and sports. Linguistic knowledge in their home language can be used to bootstrap learning in English. Studies suggest that instructional routines that draw on students’ home language, their knowledge, and cultural assets support literacy development in English. Some examples of practices used in studies include previewing and reviewing materials in children’s home language, providing opportunities for students to engage in conversations around text with peers using their home language when needed, giving definitions for key vocabulary terms in both English and their home language, and introducing key concepts by connecting them to students’ knowledge or experience in the home and community.

Teachers who don’t speak the language of their students shouldn’t be apprehensive about using these types of practices. Many technologies assist in translating words and definitions, and peers can be used as supports by grouping students with a common home language together for discussions, then asking each group to summarize their discussion in English. Further, as teachers practice a dynamic interaction style with students, they will learn about students’ lived experiences which, in turn, can be used to connect lesson content to what students know and have experienced.

Capitalizing on students’ linguistic and experiential assets by linking them to content, materials, and activities has motivational and engagement benefits and contributes to EL students’ sense of belonging and well-being.

Reading foundations. Much has been written recently about the science of reading , a discussion that spans decades. However, little research specifically addresses English-learners and how teaching reading may or may not differ for this population. Goldenberg (2020) conducted a review of research on reading and English-learners. He summarizes the findings and draws several conclusions. First, learning to read is similar for English-learners and English-speaking students. EL students must learn the same foundational skills as English-proficient students. As Goldenberg says, “Full-fledged literacy certainly requires more, but there is a reason this group of skills is called foundational: It is required for the literacy edifice under construction. As with any building, if all you have is a foundation, you do not have much. Yet, a solid foundation is still essential” (p.133).

Secondly, along with foundational skills, additional supports are required for EL students so that instruction in English is made comprehensible to them. They need additional instruction in the vocabulary found in text, especially for beginning speakers who are learning to recognize new words as they are read. Also beneficial is additional repetition and rehearsal as well as opportunities to practice. Specifically, beginning readers need practice in developing oral language, primarily in the form of effective ELD instruction to boost English proficiency.

Lastly, as EL students advance through the grades, the academic language required to navigate grade-level texts and the disciplinary knowledge students need to comprehend texts become increasingly complex and demanding. Oral English-language instruction and support needs to match the level of challenge for these students, particularly in language-intensive subjects.

Future research

Developing English proficiency arguably has the greatest impact on success in school. Understanding and responding to the specific ways that academic language is most efficiently developed might offer ways for teaching ELD most effectively and result in accelerated English acquisition. Current studies show the importance of oral language for ELs to improve early literacy, but which components of the interventions were most impactful remain unknown.

Secondly, the effects of different instructional arrangements on EL students’ achievement should be explored. Debate continues around issues such as whether pullout or push-in services are more effective, the optimal amount of time devoted to ELD instruction, and whether to group ELs together or with English-speaking peers. These are areas of practice that warrant investigation.

Thanks to Beth and Jana for contributing their thoughts.

Consider contributing a question to be answered in a future post. You can send one to me at [email protected] . When you send it in, let me know if I can use your real name if it’s selected or if you’d prefer remaining anonymous and have a pseudonym in mind.

You can also contact me on Twitter at @Larryferlazzo .

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A Case for Case Study Research in Education

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This chapter makes the case that case study research is making a comeback in educational research because it allows researchers a broad range of methodological tools to suit the needs of answering questions of “how” and “why” within a particular real-world context. As Stake (1995) suggests, case study is often a preferred method of research because case studies may be epistemologically in harmony with the reader’s experience and thus to that person a natural basis for generalization.

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Bassey, M. (1999). Case study research in educational settings . Buckingham, England: Open University Press.

Google Scholar  

Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report , 13(4), 544–559.

Becker, H. S. (2000). Generalizing from case studies. In E. W. Eisner & A. Peshkin (Eds.), Qualitative inquiry in education: The continuing debate (pp. 233–242). New York, NY: Teachers College Press.

Corcoran, P. B., Walker, K. E., & Wals, A. E. (2004). Case studies, make-your-case studies, and case stories: A critique of case-study methodology in sustainability in higher education. Environmental Education Research , 10(1), 7–21.

Article   Google Scholar  

Creswell, J. (2002). Research design: Qualitative, quantitative and mixed method approaches . London, England: Sage.

Grauer, K. (1998). Beliefs of preservice teachers in art education. Studies in Art Education, 39(4) , 350–370.

Grauer, K., Irwin R. L., de Cosson, A., & Wilson, S. (2001). Images for understanding: Snapshots of learning through the arts. International Journal of Education & the Arts , 2(9). Retrieved from http://www.ijea.org/v2n9.

Guba, E. (1981). Criteria for assessing the trustworthiness of naturalistic inquiries. Educational Resources Information Center Annual Review Paper, 29 , 75–91.

Hancock, D. R., & Algozzine, B. (2006). Doing case study research: A practical guide for beginning researchers . New York, NY: Teachers College Press.

Henderson, J. (2001). Reflective teaching: Professional artistry through inquiry (3rd ed.). Upper Saddle River, NJ: Merrill/Prentice Hall.

Klein, S. (Ed.). (2003). Teaching art in context: Case studies for art education. Reston, VA: National Art Education Association.

Lather, P. (1992). Critical frames in educational research: Feminist and poststructural perspectives. Theory into Practice , 31(2), 87–99.

Lincoln, Y. S., & Guba, E. A. (1985). Naturalistic inquiry . Beverly Hills, CA: Sage.

Merriam, S. B. (1998). Case study research and case study applications in education . San Francisco, CA: Jossey-Bass.

Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded source book (2nd ed.). Thousand Oaks, CA: Sage.

Patton, M. (1990). Qualitative evaluation and research methods (2nd ed.). Newbury Park, CA: Sage.

Richards, L., & Richards, T. (1994). From filing cabinet to computer. In A. Bryman & R. G. Burgess (Eds.), Analysing qualitative data (pp. 146–172). London, England: Routledge.

Chapter   Google Scholar  

Richards, T. J., & Richards, L. (1998). Using computers in qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), Collecting and interpreting qualita¬tive materials (pp. 445–462). London, England: Sage.

Stake, R. E. (1995). The art of case study research . Thousand Oaks, CA: Sage.

VanWynsberghe, R., & Khan, S. (2007). Redefining case study. International Journal of Qualitative Methods , 6(2), 80–94. Retrieved from http://ejournals.library.ualberta.ca/index.php/IJQM/article/view/542.

Yin, R. K. (2003). Case study research: Design and methods (3rd ed.). Thousand Oaks, CA: Sage.

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Grauer, K. (2012). A Case for Case Study Research in Education. In: Klein, S.R. (eds) Action Research Methods. Palgrave Macmillan, New York. https://doi.org/10.1057/9781137046635_4

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The 10 Most Significant Education Studies of 2023

Following our annual tussle with hundreds of studies of merit, we’ve pared them down to 10 you shouldn’t miss—from what AI can (and can’t) do to the neuroscience of brain synchrony.

For those of us hoping for a quiet, back-to-normal kind of year, the research coming out of 2023 might disappoint. A rising tide of teenage mental health issues sent researchers scurrying for answers, and the sudden ascendance of AI posed a new threat to codes of academic conduct and caused some educators to forecast the end of teaching as we know it (we’re here to dispel that myth).

There was plenty of good news in the mix—and fascinating news, too. Neuroscientists continued to push the envelope on mapping the human brain, using cutting-edge technology to get a sneak peek at the “brain synchrony” between students and teachers as they learn about complex topics, and a comprehensive review of social and emotional learning confirmed, once again, that there’s no substitute for caring, welcoming school environments.

Finally, we did our due diligence and unearthed classroom strategies that can make a big difference for students, from the use of math picture books to a better, more humane way to incorporate tests and games of knowledge into your classroom activities.

1. AI MAY CUT AN EDUCATOR’S PLANNING TIME DRAMATICALLY

In case anyone thought the jury was still out on the Turing test, which proposes a hypothetical threshold at which humans and machines respond indistinguishably to a prompt— more evidence recently came in, and it’s becoming increasingly difficult to tell who’s testing who.

Researchers from the University of North Carolina set a “deep neural” AI model to work on a college-level anatomy and physiology textbook, after first training the software to recognize important information. The AI took stock, pondered in its fashion, and then dutifully produced 2,191 test questions tied to learning standards, which a panel of teachers judged to be “on par with human-generated questions in terms of their relevance to the learning objectives.” Remarkably, the instructors also said they’d consider adopting the machine-generated questions for their courses.

That’s spooky, but not without its silver linings. Test creation is time-consuming for teachers, and one knowledgeable educator who took AI for a test drive says that it performs well on other tasks like planning lessons, writing instructions, and even composing emails to parents. New AI-powered tools like Diffit, Curipod, and MagicSchool.ai, meanwhile, are starting to sound like revolutionary teaching aids.

Concern that the end of human teaching is one software release away is premature: Studies we’ve reviewed suggest that AI still requires a lot of fine-tuning, and in July of 2023 , researchers concluded that without human intervention, AI is atrocious at mathematics, performing poorly on open-ended problems and routinely flubbing even simple math calculations. To be useful, it turns out, AI may need us more than we need it.

2. A FASCINATING GUIDE TO BETTER QUIZZING

No one likes tests—except the three authors of a 2023 study , apparently. The trio, who have experience as teachers and researchers, sing the praises of virtually every kind of test, quiz, and knowledge game, asserting that such assessments should be frequent, low-stakes, highly engaging, and even communal. Their rationale: When properly designed and stripped of dread, tests and quizzes dramatically improve “long-term retention and the creation of more robust retrieval routes for future access,” a well-established phenomenon known as the testing effect .

The study is a fascinating, granular look at the mechanics of testing and its impacts on learning. Here are some of the highlights:

Mix it up: To maximize student engagement, quiz students frequently—but don’t let the format get stale. In their analysis, the authors endorse testing formats as varied as multiple choice, cued-recall tests, clickers, fill-in-the-blank, short answer, and contests of knowledge.

Be competitive: When designing multiple-choice or true-false tests, opt for “competitive alternatives” in your answers. For example, when asking “What is the hottest terrestrial planet?,” proffer Venus , Mars , and Mercury instead of Venus , Uranus , and Saturn —because “Uranus and Saturn aren’t terrestrial planets.” Competitive alternatives require students to scrutinize all options, the authors hypothesize, leading them to retrieve and consider more learned material.

Pretest: Quizzing students on material they haven’t yet learned improves long-term performance “even if [students] are not able to answer any of those questions correctly,” according to the researchers. Notably, pretesting can also lead to “a reduction in mind wandering” during subsequent lessons.

Get communal: Asking students to take tests in groups can improve retention and motivation while reducing anxiety. Consider focusing on specific rather than open-ended questions, the authors caution, since students can sometimes “recall and remember information less accurately” when working together.

Pass it on: Teach students to self-test by “summarizing the main points from a lecture… without looking at any notes,” or by meeting in “small study groups where the students practice testing one another—an activity that many students already report doing.”

3. HOW TONE OF VOICE CHANGES CLASSROOM CULTURE

Like the proverbial canary in the coal mine, subtle shifts in a teacher’s tone of voice—a sharp rise in volume or a sudden barrage of repeated instructions born of frustration—can be the first sign that something’s awry in the classroom, disturbing a fragile equilibrium and leading students to clam up or act out, a study published late in 2022 suggests.

Researchers observed as teens and preteens listened to instructions given by teachers—“I’m waiting for people to quiet down” or “It’s time to tidy up all of your belongings,” for example—delivered in warm, neutral, or controlling tones. While the effect was unintended, an authoritative tone often came off as confrontational, undermining students’ sense of competence and discouraging them from confiding in teachers. Warm, supportive tones, on the other hand, contributed to a classroom environment that reinforced learning across multiple social and academic dimensions like sense of belonging, autonomy, and enjoyment of the class. 

It takes years to find the right tonal balance, says experienced middle school teacher Kristine Napper. “Neither high expectations nor kind hearts can do the job alone,” she coaches . Instead, teachers should strive for a warm, supportive tone and then draw on that “wellspring of trust to hold students to high standards of deep engagement with course content.”

4. BRAINS THAT FIRE TOGETHER WIRE TOGETHER

In 2021, we reported that as students progressed through a computer science course, the learning material left neural fingerprints that mirrored brain activity in other students, the teacher, and experts in the field. “Students who failed to grasp the material,” we wrote, “exhibited neural signatures that were outliers; they were drifting.” But the brain patterns of students who performed well on a later test aligned strongly with other top performing students—and with the teacher and experts, too.

Intriguingly, even abstract concepts—those that lack any physical attributes—appeared to trigger similar mental representations in students’ minds, attesting to the remarkable cognitive flexibility underlying human communication and knowledge sharing.

A 2023 study using electroencephalography (EEG) largely confirms those findings. High school science teachers taught groups of young adults fitted with electrodes about science topics such as bipedalism, habitats, and lipids. Researchers found that stronger “brain synchrony” between peers—and between students and teachers—predicted better academic performance on follow-up tests, both immediately and a full week later.

Together, these studies underscore the importance of scholarly expertise and direct instruction, but also hint at the downstream power of peer-to-peer and social learning. As knowledge passes from teachers to learners to greater and lesser degrees—some students grasp material quickly, others more slowly—an opportunity to distribute the work of learning emerges. When advanced students are paired with struggling peers, assisted by nudges from the teacher, groups of students might eventually converge around an accurate, common understanding of the material.

5. IN SUM, MATH PICTURE BOOKS WORK

The old adage that a picture is worth a thousand words—and two are worth two thousand—might be expressed, mathematically, as a simple multiplication formula. But can reading math picture books really multiply learning?

A 2023 review of 16 studies concluded that math books like Are We There Yet, Daddy? and Sir Cumference and the Dragon of Pi improved student engagement and attitudes toward math; strengthened kids’ grasp of math representations like graphs or physical models; and boosted performance on tasks like counting to 20, understanding place value, and calculating diameters. In early childhood, in particular, math picture books worked wonders—one study found that young students “tend to anticipate and guess what will happen next, resulting in high engagement, aroused interest in understanding the problems, and curiosity in finding solutions”—but even middle school students seemed mesmerized by math read-alouds.

Importantly, math picture books weren’t a substitute for procedural fluency or mathematical practice. Typically, the authors noted, teachers bracketed math units with picture books, introducing a mathematical concept “in order to prepare [students] for the upcoming practice and activities,” or, alternatively, used them to review material at the end of the lesson.

6. TO IMPROVE STUDENT WRITING, REDUCE FEEDBACK (AND PUT THE ONUS ON KIDS)

It’s hard to move the needle on student writing. Hours of close reading followed by the addition of dozens of edifying margin notes can swallow teacher weekends whole, but there’s no guarantee students know how to use the feedback productively.

In fact, without guidance, revisions tend to be superficial, a new study suggests—students might correct typos and grammatical mistakes, for example, or make cursory adjustments to a few ideas, but leave it at that. A promising, time-saving alternative is to deploy rubrics, mentor texts, and other clarifying writing guidelines.

In the study, high school students were graded on the clarity, sophistication, and thoroughness of their essays before being split into groups to test the effectiveness of various revision strategies. Students who consulted rubrics that spelled out the elements of an excellent essay—a clear central thesis, support for the claim, and cohesive overall structure, for example—improved their performance by a half-letter grade while kids who read mentor texts boosted scores by a third of a letter grade.

Rubrics and mentor texts are reusable, “increase teachers’ efficient use of time,” and “enhance self-feedback” in a way that can lead to better, more confident writers down the line, the new research suggests.

7. A NEW THEORY ABOUT THE TEEN MENTAL HEALTH CRISIS

Parents, teachers, and medical professionals are wringing their hands over the alarming, decades-long rise in teenage mental health issues, including depression, feelings of “ persistent hopelessness ,” and drug addiction.

The root causes remain elusive—cell phones and social media are prime suspects—but a sprawling 2023 study offers another explanation that’s gaining traction: After scouring surveys, data sets, and cultural artifacts, researchers theorized that a primary cause is “a decline over decades in opportunities for children and teens to play, roam, and engage in other activities independent of direct oversight and control by adults.”

Scholarly reviews of historical articles, books, and advice columns on child rearing depict an era when young children “walked or biked to school alone,” and contributed to their “family’s well being” and “community life” through meaningful chores and jobs. If that all feels vaguely mythical, data collected over the last 50 years reveals a correlation: frank admissions by parents that their children play outdoors independently less than they did, and significant drops in the number of kids who walk, bike, or bus to school alone or are allowed to cross busy roads by themselves. In the U.S., for example, a government survey showed that 48 percent of K–8 students walked to school in 1969, but by 2009 only 13 percent did.

Risky play and unsupervised outdoor activities, meanwhile, which might “protect against the development of phobias” and reduce “future anxiety by increasing the person’s confidence that they can deal effectively with emergencies,” are often frowned upon. That last point is crucial, because dozens of studies suggest that happiness in childhood, and then later in adolescence, is driven by internal feelings of “autonomy, competence, and relatedness”—and independent play, purposeful work, and important roles in classrooms and families are vital, early forms of practice.

Whatever the causes, young children seem to sense that something’s off. In one 2017 study , kindergartners who viewed images of fun activities routinely struck pictures that included adults from the category of play, rejecting the role of grown-ups in a domain they clearly saw as their own.

8. DIRECT INSTRUCTION AND INQUIRY-BASED LEARNING ARE COMPLEMENTARY

It’s an often-fiery but ultimately dubious debate: Should teachers employ direct instruction, or opt for inquiry-based learning?

At its core, direct instruction often conveys information “by lecturing and by giving a leading role to the teacher,” researchers explain in a 2023 study examining the evidence supporting both approaches. Critics typically focus solely on its passive qualities, a straw-man argument that ignores activities such as note-taking, practice quizzes, and classroom discussions. Opponents of inquiry-based learning, meanwhile, characterize it as chaotic, akin to sending students on a wild goose chase and asking them to discover the laws of physics on their own—though it can actually unlock “deep learning processes such as elaboration, self-explanation, and metacognitive strategies,“ the researchers say.

Both sides misrepresent what teachers actually do in classrooms. Instructional models are “often combined in practice,” the researchers note, and inquiry-based learning is usually supported with direct instruction. Teachers might begin a lesson by leading a review of key concepts, for example, and then ask students to apply what they’re learning in unfamiliar contexts. 

Let the debate rage on. Teachers already know that factual fluency and the need to struggle, flail, and even hit dead-ends are integral to learning. Teaching is fluid and complex and spools out in real time; it resists every effort to reduce it to a single strategy or program that works for all kids, in all contexts.

9. A TRULY MASSIVE REVIEW FINDS VALUE IN SEL—AGAIN

It’s déjà vu all over again. The researcher Joseph Durlak, who put social and emotional learning on the map with his 2011 study that concluded that SEL programs boosted academic performance by an impressive 11 percentile points, was back at it in 2023—working with an ambitious new team, led by Yale professor Christina Cipriano, on a similar mission.

The group just published a comprehensive meta-analysis that surveyed a whopping 424 studies involving over half a million K–12 students, scrutinizing school-based SEL programs and strategies such as mindfulness, interpersonal skills, classroom management, and emotional intelligence. The findings: Students who participated in such programs experienced “improved academic achievement, school climate, school functioning, social emotional skills, attitudes, and prosocial and civic behaviors,” the researchers concluded.

Intriguingly, SEL remained a powerful driver of better cultures and student outcomes into the middle and high school years, a reminder that there’s no cutoff point for building relationships, teaching empathy, and making schools inclusive and welcoming.

While politicians continue to stoke controversy on the topic, there’s actually widespread support for SEL, as long as it’s connected to better academic outcomes. A 2021 Thomas B. Fordham Institute survey revealed that parents reacted negatively to classroom instruction labeled “social and emotional learning,” but were favorably disposed when a single clause was added—calling it “social-emotional & academic learning” turned the tide and secured parental buy-in.

10. MORE EVIDENCE FOR MOVING PAST “FINDING THE MAIN IDEA”

In the United States, the teaching of reading comprehension has ping-ponged between skills-based and knowledge-based approaches. In 2019, things appeared to come to a head: While reading programs continued to emphasize transferable skills like “finding the main idea” or “making inferences,” the author Natalie Wexler published The Knowledge Gap , an influential takedown of skills-based methods, and a large 2020 study from the Thomas B. Fordham Institute concurred, noting that “exposing kids to rich content in civics, history, and law” taught reading more effectively than skills-based approaches.

Now a pair of new, high-quality studies—featuring leading researchers and encompassing more than 5,000 students in 39 schools—appears to put the finishing touches on a decades-long effort to push background knowledge to the forefront of reading instruction.

In a Harvard study , 3,000 elementary students participated in a yearlong literacy program focused on the “knowledge rich” domains of social studies and science, exploring the methods used to study past events, for example, or investigating how animals evolve to survive in different habitats. Compared to their counterparts in business-as-usual classes, the “knowledge based” readers scored 18 percent higher on general reading comprehension. Background knowledge acts like a scaffold, the researchers explained, helping students “connect new learning to a general schema and transfer their knowledge to related topics.” In the other study , a team of researchers, including leading experts David Grissmer, Daniel Willingham, and Chris Hulleman, examined the impact of the “Core Knowledge” program on 2,310 students in nine lottery-based Colorado charter schools from kindergarten to sixth grade. The approach improved reading scores by 16 percentile points, and if implemented nationally, the researchers calculated, might catapult U.S. students from 15th to fifth place on international reading tests.

The pendulum is swinging, but the researchers caution against overreach: There appear to be “two separate but complementary cognitive processes involved in development and learning: ‘skill building’ and ‘knowledge accumulation,’” they clarified. We may have the balance out of whack, but to develop proficient readers, you need both.

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• Published: 17 April 2024

How popularising higher education affects economic growth and poverty alleviation: empirical evidence from 38 countries

• Jian Li   ORCID: orcid.org/0000-0002-3228-8163 1   na1 ,
• Eryong Xue   ORCID: orcid.org/0000-0002-7079-5027 2   na1 ,
• Yukai Wei   ORCID: orcid.org/0000-0002-5202-7307 2 &
• Yunshu He   ORCID: orcid.org/0000-0003-4814-9835 2  

Humanities and Social Sciences Communications volume  11 , Article number:  520 ( 2024 ) Cite this article

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The popularisation of higher education supports UNESCO’s aim of developing inclusive and equitable quality education to achieve the fourth Sustainable Development Goal. However, the effect of popularising higher education on economic growth and poverty alleviation remains unexplored. Therefore, this study investigated the effects of higher education and adult education within populations (popularisation of higher education) on economic growth (gross domestic product; GDP) and the poverty line using panel data from 38 countries. OLS and quantile regression were performed using data for the period 1995–2021 extracted from the OECD and World Bank databases. The results showed that the population segments with higher education had a significantly positive impact on GDP growth. Moreover, an increased proportion of the population with higher education, of working age, was found to be a contributing factor to GDP growth. Popularising higher education also played a positive role during the initial stage of social and economic development. This study also highlighted that popularising higher education play a key role to influence a country’s educational development and scientific and technological innovation drives the deepening of a country’s economy. It suggested that both national and local governments worldwide should pay much attention to the popularisation degree of higher education to greatly improve the innovative ability of talents and scientific and technological innovation in higher education for both the economic growth and poverty alleviation.

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Introduction

The popularisation of higher education critically contributes to UNESCO’s efforts to realise the fourth Sustainable Development Goal of inclusive and equitable quality education (Ainscow, 2020 ; Bamberger and Kim, 2022 ).Popularisation of higher education expands the scale of higher education and its high growth rate introduces considerable challenges to the management structure of higher education, triggering a series of theoretical and practical concerns relating to the nature and function of higher education (Balestra and Ruiz, 2015 ; Brand, 2021 ). Given that education and social and economic development are mutually reinforcing, the expansion of higher education leads to an ascending spiral of development for individuals and/or economies. By contrast, a lack of education or early withdrawal from education leads to a downward spiral for them (Camilla, 2023 ). This relationship between education and development undergirds the model of poverty alleviation based on the return on education (Decancq, 2017 ). The previous studies emphasise the importance of the return on education as a multidimensional anti-poverty mechanism and thus a key factor in poverty alleviation (Fang et al., 2022 ; Chelli et al., 2022 ; Garritzmann, 2016 ). For example, return on education is the key factor enabling a transition from poverty alleviation through education to poverty alleviation through education (Gillian et al., 2021 ; Gong and Hong, 2021 ). Poverty alleviation is realised through an interlinking of these two processes and the promotion of the latter (Granata, 2022 ; Habibi and Zabardast, 2020 ). The educational resources can meet the needs of the poor mainly through the return on education at the levels of survival and life quality. In addition, the previous studies highlighted that, with a continuous expansion in the scale of higher education, its economic effect gradually appears to become marginal (Hoeller et al., 2014 ). The density of colleges and universities worldwide has increased considerably in recent years, but it is still inadequate to meet increasing demands resulting from the ongoing popularisation of higher education (Jericho, 2016 ). The increase in the number of colleges and universities has a positive effect in promoting economic development but with marginal benefits. (Julian, 2018 ).

Through reviewed the current relevant studies, it is found that there have limited studies that have simultaneously explored the effects of popularising higher education on economic growth and poverty alleviation. The previous research revealed that most studies have focused on the relations between popularisation of higher education and economic growth. However, a few empirical investigations have examined the effect of population segments with higher education and adult education (popularisation of higher education) on economic growth (GDP) and poverty reduction. Considering the scope and limitations of previous studies, it aimed to address the above research gap by investigating the effect of a population segment with high levels of higher education and adult education (popularisation of higher education) on economic growth (GDP) and the poverty line at a wide scale using panel data from 38 countries. The main research questions addressed in this study are as follows.

Q1: What is the effect of a population segment with higher education on GDP growth?

Q2: What is the effect of adult education on GDP growth?

Q3: What impact does a population segment with higher education have on reducing the proportion of those experiencing poverty?

Q4: What is the relation between an increased level of adult education and the proportion of the population experiencing poverty?

All these questions are relevant to an exploration of the effect of the population segment with higher education and adult education (popularisation of higher education) on economic growth (GDP) and the poverty line. This study is divided into several sections: the first section concentrates on examining the effect of popularising higher education on economic growth and the poverty line, the relationship between popularisation of higher education and poverty alleviation, and the relationship between popularisation of higher education and poverty alleviation. In the second section of method, to address this research gap, this study performed OLS and quantile regressions using data extracted from the OECD and World Bank databases for the period 1995–2021. An OLS regression model and a panel quantile model were used to analyse the effect of a population segment with higher education and adult education (popularisation of higher education) on economic growth (GDP) and the poverty line within 38 OECD countries. The impact of the proportion of people aged 24–64 years and 25–34 years who had completed higher education in relation to their peers on GDP and the proportion of people living in poverty in 38 OECD countries have been measured and analysed. The results and discussion have been provided at the last.

Literature review

The effect of popularising higher education on economic growth.

The population segment with higher education is regarded as an important contributor to economic growth, generating scientific knowledge and providing labour, which in turn increases human capital and productivity (Jungblut, 2017 ; Kalamova, 2020 ; Liu, 2017 ). As the scale of higher education expands, the emergence of knowledge power as a large-scale global phenomenon reflects the important role of an expanded educated labour force in the advancement of science and technology and the economy. For example, the relationship between higher education and economic development in European Union countries between 1997 and 2016 was analysed. Their findings revealed a statistically significant correlation between expanding higher education and economic growth in the selected countries. The one-way cause-and-effect relationship between education and economic development in these countries suggests that an increase in the proportion of the population enroled in higher education boosts economic performance. In addition, using a survey sample of 35 households, a retrospective study in Brazil, examined the role of educational expansion in reducing income inequality and poverty. Its findings suggest that it would take decades to reduce inequality and poverty in this country and that this outcome could only be achieved through a major expansion of the higher education sector. The growth needed to achieve this outcome would be considerable (Lamichhane et al., 2021 ). This reduction in inequality and poverty could only be achieved if optimistic assumptions about growth, matching job skills and the return on education do not fall short. In brief, education is not a panacea for reducing poverty and inequality. How three major stages of education contributed to the growth in labour productivity in 125 countries during the period 1999–2014 was also explored. They found that human capital is consistent with the educational returns of an average number of years of formal education at the levels of primary, secondary, and higher education. Their analysis showed that higher education had the greatest impact on labour productivity in the economies under study (Ledger et al., 2019 ). In addition, popularising higher education plays an important role in promoting economic growth, as the scale of higher education can guarantee the scale of human resources development by improving the quality of human resources and cultivating and distributing innovative scientific and technological talents. The scale of higher education guarantees the spread of science and technology and the popularisation of scientific and technological achievements (Mathias, 2023 ; Megyesiova and Lieskovska, 2018 ). The expanded scale of higher education worldwide has a spatial spillover effect on economic growth, which is strengthened through international cooperation in the fields of science and technology.

Popularising higher education also plays a direct role in cultivating and transporting scientific and technological talents to promote international scientific and technological cooperation (Mitic, 2018 ; Özdoğan Özbal, 2021 ; OECD, 2022 ; Pinheiro and Pillay, 2016 ). The scale of postgraduate education inhibited the total number of scientific and technological innovation achievements, indicating that there may be a trade-off between ‘quantity expansion’ and ‘quality upgrading’ of scientific and technological innovation achievements. Nevertheless, the positive effect on the number of high-tech innovation outcomes is significant, indicating that the supporting effect of graduate education on scientific and technological innovation is mainly concentrated in the high-tech fields (Pinheiro and Pillay, 2016 ; Rowe, 2019 ; Sahnoun and Abdennadher, 2022 ). The ‘talent increment’ of regional expansion and the ‘resource stock’ of graduate education have a combined promoting effect on high-tech innovation. There are differences in the effect of graduate education supporting high-tech innovation among provinces with different characteristics relating to the development of graduate education. The incremental expansion of high-quality talent is essential for enhancing the efficiency of material capital and stabilising the advantage of resource stocks. Using education statistics from OECD countries, Russia, and several other countries that participate in OECD education research, comparative and correlational analysis methods were applied to analyse how the scale of growth in young people’s participation in higher education is reflected in changes in their employment and economic activity. The results of their analysis showed that the growth in economic activity involving young graduates with a master’s degree exceeded that of college graduates after the 2009 financial crisis, and graduates fared better in the 2020 crisis, which was triggered by the COVID-19 pandemic.

The effect of popularisation of higher education on poverty alleviation

Popularisation of higher education is regarded as an essential factor contributing to poverty alleviation (Samo, 2022 ; Adams, 2013 ; Zapp, 2022 ). The higher education’s role in promoting economic growth can only be fully realised through the cultivation of talents suitable for the actual development situation of the country. Countries with food shortages, for example in Africa, also need to procure and train the right agricultural talent. Key drivers of sustainable agricultural production include access to improved technologies, sustainable growth of human, biological and natural resource capital, improvements in institutional performance and a favourable economic policy environment. Higher education graduates with the necessary ‘soft skills and business skills constitute an important pillar. Chakeredza ( 2008 ), who explored the effect of popularising higher education on poverty alleviation, suggested that the number of hungry people in Africa will continue to increase. Higher education in agriculture must be transformed, and efforts must focus on retaining faculty and on reviewing and redesigning institutional management systems, curriculum content and education delivery.

There are many reasons for poverty, with a lack of education being an important one. Insufficient quality education leads to educational poverty. Using PISA data, Agasisti et al. ( 2021 ) investigated the extent of educational poverty in European countries, considering its incidence, breadth, depth and severity. For this study, they adopted an additive multidimensional poverty measure proposed by Alkirew and Foster. Their findings indicated that between 2006 and 2015, the depth and severity of poverty decreased in most of the countries under study. Moreover, the incidence of educational poverty in many European countries was related mainly to student characteristics and school factors. The expansion of higher education has a positive effect on economic development and poverty reduction by improving work skills within the labour force. Increased enrolment in higher education encourages individuals born in families with low education levels to avail of higher education opportunities. Evidently, the expanded scale of higher education in the process of promoting economic growth has enhanced the equity effect of intergenerational social mobility. The expansion of higher education improves total factor productivity, thus promoting economic transformation and advancement globally (Samo, 2022 ; Adams, 2013 ; Zapp, 2022 ). Furthermore, the previous studies have shown that the structure of higher education talent training has a significant impact on economic development. Therefore, government departments need to make constant efforts to improve relevant systems and promote the optimisation and upgrading of the structure of higher education talent training to meet the needs of future economic development.

Theoretical underpinnings

The relationship between education and economic growth is a classic issue in the study of educational economics. For example, in Solow’s view, the growth of per capita output comes from per capita capital stock and technological progress, but capital investment has the problem of diminishing marginal returns, and the long-term sustainable development of the economy depends on technological progress (Solow, 1957 ). The emphasis on technological progress is a very important point in Solow’s growth theory. It was Schultz who systematically analyzed the contribution of education to economic growth. Influenced by the progress of economic growth theory and national accounting methods, Schulz proposed human capital theory in the process of explaining Solow residuals (Schultz, 1961 ). believes that once human capital is included in economic growth, it will solve the paradoxes and puzzles faced in economic growth research. Starting with the difference in income of different types of workers in the labour market, he found that education and health factors are the main reasons for the income difference, and further clarified that the reason for the income difference is the difference in labor productivity (Schultz, 1961 ). Schultz ( 1961 ) believes that human resources include the quantity and quality of labor, and he mainly focuses on the skills and knowledge of people who can improve labor productivity. As for how to measure human capital investment, Schulz believes that the cost of human capital can be measured in the same way as physical capital. Lucas ( 1988 ) focuses on the mechanism of human capital accumulation and why human capital does not show diminishing marginal returns like physical capital. Lucas divides the effect of human capital into internal effect and external effect. Romer ( 1990 ) internalised technological progress, revealed the relationship between human capital and technological progress, and proposed that the stock of human capital determines the economic growth rate, and it is human capital rather than population that determines economic growth. Romer starts with three hypotheses: first, technological progress is central to long-term economic growth; Second, technological progress is formed by people’s response to market incentives, and market incentives determine technological progress. Third, technology is a special kind of product, and once the cost of the initial input is produced, the technology can be reproduced indefinitely at no cost or very low cost.

In other words, higher education is more about improving students’ ability and productivity, thereby increasing students’ income, and promoting economic growth. Higher education mainly affects economic growth through two aspects: one is the same as Schulz’s improvement of individual ability, and the internal effect of human capital, which directly affects the production process (Schultz, 1961 ). Second, Lucas emphasised the external effect of human capital, and the comprehensive effect of human capital on the whole society, which has the characteristics of increasing marginal benefit (Lucas, 1988 ). It emphasises that the human capital invested in technological innovation and the existing knowledge and technology stock of the whole society jointly determine technological innovation.

Research hypotheses and analytical model

In this study, an OLS regression model and a panel quantile model were used to analyse the effect of a population segment with higher education and adult education (popularisation of higher education) on economic growth (GDP) and the poverty line within 38 OECD countries. The study’s hypotheses were as follows:

Hypothesis 1: The effect of a population segment with higher education has a positive impact on GDP growth.

Hypothesis 2: Some level of adult education has a positive impact on GDP growth.

Hypothesis 3: A population segment with higher education has a positive impact by reducing the proportion of the population experiencing poverty.

Hypothesis 4: An increase in the level of adult education has a positive impact by reducing the proportion of the population experiencing poverty.

The widely used Mankiw-Romer-Weil model was applied in this study. The overall level of development of higher education and the popularisation of higher education were considered core elements that independently promote economic development and alleviate poverty. The following model was constructed by incorporating the variable of quality higher education into the Solow model:

where Y it refers to the output of i country in t year. The independent variables Qit and P it respectively represent the scale of development and the degree of popularisation of higher education in i country in t year. The following specific model was constructed:

The independent variables were the proportion of people aged 25–64 years with higher education (A) and the proportion of people aged 25–34 years with higher education within the same age group (B). The first variable reflects the population segment that has completed higher education and can work in the corresponding age group. The second reflects the degree of popularisation of higher education. The proportion of those who have completed higher education in relation to their peers is in the normal state, which can reflect the enrolment rate for the previous process of higher education, thus indicating the degree of popularisation of higher education.

The dependent variables were GDP and the poverty line (D). GDP is a measure the overall level of a country’s economic and social development. The poverty line refers to the proportion of people living on less than US$1.25 a day as a percentage of the country’s total population or the proportion of people living in poverty. Thus, it reflects the level of equity in social development. The figure of US$2.15 is used in the World Bank’s index and is based on the purchasing power parity in 2017 (see Table 1 ).

Data sources and selection of variables

This study measured the impact of the proportion of people aged 24–64 years and 25–34 years who had completed higher education in relation to their peers on GDP and the proportion of people living in poverty in 28 OECD countries. Specifically, this study assessed the impact of the overall level of development of higher education and the degree of its popularisation (the breadth of development of higher education) on GDP (the height of development of economic and social development) and the poverty line (the breadth of development of economic and social development). Data were sourced from the OECD database and the World Bank website covering the period 1995–2021. This study selected 38 OECD countries for this study: the United States, UK, France, Germany, Italy, Canada, Ireland, the Netherlands, Belgium, Luxembourg, Austria, Switzerland, Norway, Iceland, Denmark, Sweden, Spain, Portugal, Greece, Turkey, Japan, Finland, Australia, New Zealand, Mexico, the Czech Republic, Hungary, Poland, South Korea, Slovakia, Chile, Slovenia, Estonia, Israel, Latvia, Lithuania Colombia and Costa Rica. Figure 1 shows the distribution of the 38 OECD countries. Of these countries, 20 were founding members of the OECD when it was established in 1961, while the remaining 18 subsequently became members. After 1994, OECD membership expanded rapidly. Five new members were added within three years. OECD then entered a period of accelerated development, and its operations and advancement reached an optimal stage. Therefore, this study selected data from the OECD database and the World Bank website covering the period 1995–2021 to explore the relationship between higher education and economic and social development in OECD member countries.

It expresses the geographical relations of the Atlantic region and simplifies the latitude and longitude lines and country symbols, highlighting the geographical distribution by highlighting OECD countries in color and other countries in apricot color.

The impact of the population segment with higher education on GDP growth

This study explored the impact of the population segment with higher education on GDP, taking the proportion of people aged 25–34 years who had completed higher education (B) and the proportion of people aged 25–64 years who had completed higher education (A) as the independent variables for the OLS regression. The square value of model R was 0.097, indicating that the two independent variables could explain 9.73% of the change in GDP. The model passed an F test ( F  = 46.137, p  = 0.000 < 0.05), indicating that at least one of the two independent variables impacted the GDP regression coefficient (C). The following formula was used:

The final analysis revealed that the regression coefficient value of A was 1.553 and the significance level was 0.01 ( t  = 7.141, p  = 0.000 < 0.01). Therefore, A had a significantly positive influence on C. Accordingly, the proportion of the population aged 25–64 years who had completed higher education, that is, the overall level of development of higher education was found to have a positive impact on GDP. The influence coefficient value was 1.533, indicating that an increase in the proportion of the population with completed higher education led to an increase in GDP.

The regression coefficient value of B was −0.813 at a 0.01 level of significance ( t  = −4.300, p  = 0.000 < 0.01), indicating that B had a significantly negative influence on C. The proportion of the population aged 25–34 years who had completed higher education, that is, the degree of popularisation of higher education had a negative effect on GDP, and the influence coefficient value was −0.813.

The negative impact on economic and social development caused by an increase in the popularity of higher education and the proportion of young people’s higher education experience may be attributed to the excess capacity of higher education. The development of higher education should be adapted to the national context. An excess of higher education and a lack of investment lead to a rise in the social cost of education and a decline in social outputs, which hinder social and economic development. At the same time, young people aged between 25 and 34 years occupy the position of’ export’ in the education process. With the increasing popularity of higher education, the supply of talents in the labour market generated through the recruitment of former higher education exceeds the demand for graduates with higher education within recruiting organisations. Consequently, issues such as wasted educational resources and knowledge, unemployment, excessive education, excess talents, an imbalance in the structure of higher education, excessive expansion and decreasing compatibility undermine economic operations and hinder GDP growth.

In this study, the variance decomposition and Pearson coefficient based on covariance calculation were analyzed. The variable of the number of 25–34-year-old who have completed higher education as a percentage of their peers explains 50.74% of the change in GDP. The variable of the proportion of 25–64-year-old who have completed higher education explains 49.26% of the change in GDP. The variable of 25- to 34-year-olds who completed higher education as a percentage of their peers explained 45.88% of the change in poverty line. The variable of the proportion of people aged 25–64 who have completed higher education explains 54.12% of the change in GDP (See Table 2 ).

The proportion of people aged 25–34 who have completed higher education in their peers and the proportion of people aged 25–64 who have completed higher education in their peers, GDP and poverty line showed significant correlation coefficients. The correlation between the proportion of people who have completed higher education at the age of 25–34 and the proportion of people who have completed higher education at the age of 25–64 is 0.931, and shows a significance of 0.01, which indicates that there is a significant positive correlation between the proportion of people who have completed higher education at the age of 25–34 and the proportion of people who have completed higher education at the age of 25–64. The correlation between the proportion of the number of people who have completed higher education at the age of 25–34 and the GDP is 0.209, and the significance is 0.01, which indicates that there is a significant positive correlation between the number of people who have completed higher education at the age of 25–34 and the GDP. The correlation between the number of people who have completed higher education and the poverty line at the age of 25–34 is −0.365, with a significance of 0.01, indicating a significant negative correlation between the number of people who have completed higher education and the poverty line at the age of 25–34 (See Table 2 ).

White test and BP test were used in this study. The test null hypothesis is that the model has no heteroscedasticity. The table above shows that both tests reject the null hypothesis ( p  < 0.05), indicating that the model does have heteroscedasticity. When there is a heteroscedasticity problem, Robust and robust standard false regression is used (See Table 3 ).

The impact of a population segment with higher education on the poverty line

This study also explored the impact of a population segment with higher education on the poverty line. Specifically, this study performed an OLS regression in which the proportion of people aged 25–34 years who had completed higher education (B) and the proportion of those aged 25–64 years who had completed higher education (A) were the independent variables. As Table 2 shows, the R squared value was 0.134. This means that variables A and B could explain 13.37% of the change in the poverty line (D). The model passed the F test ( F  = 48.771, p  = 0.000 < 0.05), which means that at least one variable (A or B) had an impact on the poverty line. The formula for the change in the poverty line was expressed as follows:

The final analysis revealed that the regression coefficient value of the proportion of people aged 25–64 years who had completed higher education (A) was 0.005 but with no significance ( t  = 0.428, p  = 0.669 > 0.05), indicating that the population segment with higher education did not have an impact on the poverty line.

The regression coefficient value of the proportion of people aged 25–34 years who had completed higher education (B) was −0.048 at a significance level of 0.01 ( t  = −4.305, p  = 0.000 < 0.01), which means that in relation to their peers, the proportion of people aged 25–34 years who had completed higher education had a significantly negative impact on the proportion of poor people. A higher proportion of people aged 25–34-years who had completed higher education corresponded to a higher penetration rate of higher education and a lower proportion of those living in poverty. This phenomenon can be attributed to OECD’s support for the development of higher education in various countries. When the development of higher education reaches a certain level, the reduction of the proportion of the population segment experiencing poverty will no longer be affected by a simple expansion of the scale of extended higher education and the superposition of the total number of highly educated human resources. It will be influenced more by the reasonable distribution of educational resources and educational equity within higher education and its popularisation, that is, the increase in the proportion of the school-aged population aged 25–34 years based on the increase of the previous enrolment rate (see Table 4 ).

The effect of adult education on GDP growth

For quantile regression analysis, a total of nine models (with decimal points ranging from 0.10 to 0.90 and at intervals of 0.10) were estimated in this analysis, which aimed to explore the impact of the independent variables A and B on the dependent variable, GDP (C). When the quantile value was between 0.1 and 0.3, the proportion of the population aged 25–64 years who had completed higher education (A) had no significant positive impact on GDP growth, indicating that the development of higher education did not significantly affect economic and social development in poorer OECD countries. When the quantile value was between 0.4 and 0.6, the level of development of higher education had a significantly negative impact on economic and social development. Thus, for a country that had developed over a period, the advancement of higher education required multiple inputs, such as capital, material, and human resources.

During the early stage of the development of higher education, such inputs may, however, have a negative and weakening impact on social and economic development. The added cost of education and the lag between the output of educational achievements and the input of talents puts increased pressure on economic and social development during a certain period. When the quantile value was 0.7 or higher, the improvement of the overall level of higher education had a significantly positive impact on GDP growth, indicating the realisation of the talent training outcomes of higher education. Teaching and research outcomes were thus transformed into socially productive resources and power, with talents with higher education contributing to economic and social development.

When the quantile value was 0.1, the proportion of people aged 25–34 years who had completed higher education in relation to their peers (variable B), indicating the popularisation of higher education, had no significant impact on GDP growth. Thus, in extremely backward countries, the popularisation of higher education had little effect on economic and social development. When the quantile value ranged between 0.2 and 0.6, the popularisation of higher education had a significantly positive effect on GDP growth, indicating its contribution to economic growth.

When the quantile value was 0.7, the influence of variable B on variable C was no longer significant, indicating that social development would soon face the problem of overcapacity in higher education. When it exceeded 0.7, the ratio of eligible people aged 25–34 years who had completed higher education in relation to their peers had a significantly negative impact on GDP growth, revealing that with the development of the economy, society and education, higher education had become overexpanded. Thus, the cost of investing in education exceeded the social benefits, leading to overcapacity whereby the supply of higher education talents exceeded the demand. This situation led to wasted educational resources and excessive competition of talents, hindering economic growth (See Table 5 ).

The increased level of adult education and the proportion of the population experiencing poverty

Using the same model, this study explored the influence of the independent variables, A and B, on the poverty line (dependent variable D). The proportion of the population aged 25–64 years who had completed higher education (independent variable A) had no significant influence on the proportion of the population living in poverty, indicating that popularisation of education and economic and social development have been achieved to a certain extent in OECD countries, and improvements targeting the population experiencing poverty could no longer be achieved simply by increasing the volume and quantity of higher education. When the quantile value was 0.1, the proportion of people aged 25–34 years who had completed higher education in relation to their peers (independent variable B) had no significant effect on the proportion of the population experiencing poverty (dependent variable D). Therefore, the strategy of increasing higher education enrolment and the ratio of the eligible population through the fair allocation of educational resources, and thus the popularisation of education, would not be effective for a small population segment experiencing poverty. In other words, the population segment experiencing poverty in highly developed countries is less receptive to the popularisation of higher education. When the quantile value was 0.2, the independent variable, B, had a significantly positive impact on the dependent variable D, that is, an increase in the popularity of higher education led to an increase in the population segment experiencing poverty. This phenomenon can be interpreted as reflecting the inherent disadvantages of the welfare state in the field of education. A rise in the number of eligible young people aged 25–34 years who have completed higher education reflects the development trend of higher education towards fairness and popularisation following the redistribution of higher education resources.

The fair distribution of higher education resources leads to a lack of competition in the areas of teaching and career development. To a certain extent, reducing students’ willingness and enthusiasm to work may lead to poverty caused by the failure to achieve teaching results. When the quantile value was between 0.3 and 0.4, the independent variable, B, had no significant influence on the dependent variable D. In relatively poor countries, the popularisation of higher education contributes little to reducing the degree of poverty, so it may be necessary to explore ways of alleviating poverty from the perspective of improving the overall level and expanding the scale of basic higher education. When the quantile value was 0.5 or above, the independent variable B had a significantly negative impact on the dependent variable D, indicating that for countries with a relatively high proportion of their population experiencing poverty, the following strategy would be more effective.

Considering the quantile data, this study deemed that the degree of sensitivity of countries at different stages of economic development to the level of development and popularisation of higher education could be more intuitively evaluated using a radar map (see Fig. 2 ). Countries with sub-points 0.1–0.9 were defined along a spectrum as extremely backward, backward, moderately backward, slightly backward, moderate, preliminarily developed, moderately developed, developed, and highly developed. From the perspective of economic development, increasing the proportion of young people who complete higher education and popularising higher education had an obvious positive effect in backward and medium-developed countries, whereas the effect in highly developed countries was not obvious. Overall, the sensitivity of OECD countries to the high level of education penetration was found to be higher than the level of development of higher education. From the perspective of equitable economic development, the overall level of development of higher education had no significant impact on the poverty link in OECD countries, whereas OECD countries with differing economic development backgrounds and at varying stages of development evidenced relatively significant and stable sensitivity to the proportion of young and middle-aged people who completed higher education and the popularisation of higher education.

The dashed line represents the proportion of people aged 25–34 years who have completed higher education. The solid line represents the proportion of people aged 25–64 years who have completed higher education, the impact of the overall level of higher education.

Our findings indicated that population segments with higher education had a significantly positive impact on GDP growth in 38 OECD countries. An increase in the proportion of the population segment of working age who completed higher education was found to contribute to GDP growth. Moreover, an improvement in the popularity of higher education played a positive role during the initial stage of economic and social development.

At the same time, oversupply and overcapacity may result from a continuous improvement of higher education. A very large number of young people who have completed higher education can lead to excessive competition and wasted academic qualifications (Mathias, 2023 ; Megyesiova and Lieskovska, 2018 ). In turn, higher education knowledge unemployment, overinvestment, a structural imbalance, disorderly expansion and wasted resources can occur, which have detrimental impacts on economic operations.

Some studies have shown that strengthening the quality of higher education helps to improve cognitive abilities within the labour force, thereby enhancing the growth of the knowledge economy (Ainscow, 2020 ; Bamberger and Kim, 2022 ). Other studies have reported regional heterogeneity relating to the marginal effect of improving the quality of higher education on economic growth. Some scholars have analysed the influence of the quality of higher education on economic development from the perspective of human capital investment theory. Their findings indicate that the quality of higher education determines the composition and growth trend of social human capital. Because of differences in the degrees of development of different economies, the quality of higher education has a phased influence on economic growth (Balestra and Ruiz, 2015 ; Brand, 2021 ). Case studies of African developing countries by international scholars have revealed that quality factors are key to realising the economic development function of higher education. From the perspectives of both efficient financial investments by states in education poverty alleviation and the effects of economic, time and emotional investments of poor families and individuals in education poverty alleviation, it is necessary to take the return on education into consideration. Moreover, it is important to respond to reasonable concerns regarding the return on education for poor people and to strengthen their cognitive capacities to rationalise as well as their expectations regarding returns on education (Li et al., 2023 ). In this way, the intention to participate and behaviour of anti-poverty education will be generated, and the strategic upgrading of poverty alleviation combined with the promotion of aspirations and cognitive capacities will be emphasised.

Implications

Our use of panel data from 38 countries to deepen understanding of the effect of popularising higher education on economic growth and poverty reduction also has practical implications. The economic, social, and higher education undertakings in OECD countries evidence a certain level of development. The population segment with higher education has no significant impact on reducing the proportion of the population segment experiencing poverty. Simply increasing the proportion of people who complete higher education and expanding the scale of higher education will not effectively reduce poverty (Li and Xue, 2021 ). Providing more educational opportunities to poor people through the slanting of educational resources can help to reduce the proportion of poor people (Ainscow, 2020 ; Bamberger and Kim, 2022 ). For example, popularising higher education plays a key role to influence a country’s development level and scientific and technological innovation drives the deepening of a country’s economy (Bamberger and Kim, 2022 ). Technological progress is the core of economic growth, scientific and technological innovation brings technological change and development in all aspects, human capital promotes economic growth, and higher education trains talents and improves the capital attribute of human (Camilla, 2023 ). For endogenous economic growth theory, the economy does not rely on external forces to achieve sustained growth, and endogenous technological progress determines sustained economic growth. Popularising higher education worldwide brings the accumulation of human capital, improves the quality of workers, and scientific and technological innovation makes technological progress and high-quality economic development, practically. Human capital accumulation is also the process of continuous input of labour force, which covers the accumulation of human capital by labour force factors in formal education, training, and other learning processes. From the perspective of human capital, popularising higher education is the most direct and efficient way to promote the accumulation of human capital and improve the quality of labour force (Balestra and Ruiz, 2015 ; Brand, 2021 ). The popularisation degree of higher education is one of the important indicators to measure the development level of a country’s economic, and it is also the common trend of the development of higher education in all countries after World War II. In this transitional era, how to continue the achievements of higher education in the popular era and solve the existing problems as soon as possible is the heavy responsibility of our times. Therefore, at the initial stage of popularisation of higher education, it is necessary to re-examine the process of higher education popularisation globally and explore the internal logics between the popularisation of higher education and Sustainable Development Goal of inclusive and equitable quality education (Ainscow, 2020 ; Bamberger and Kim, 2022 ).

For policy suggestions, this study suggests that both national and local governments worldwide should pay much attention to the popularisation degree of higher education to greatly improve the innovative ability of talents and scientific and technological innovation in higher education. For example, they could promote scientific and technological innovation in an organised manner to serve national and regional economic and social development. Faced with the current situation in which global higher education has entered a stage of popularisation and new challenges and problems in serving regional economic and social development, national governments should continue to optimise the distribution and structure of higher education resources to support different regions, focusing on the major strategy of enhancing national competitiveness, serving economic and social development, and promoting common prosperity.

Contributions

This study novelty contributes on examining how popularising higher education affects economic growth and poverty alleviation, conceptually, methodologically, and practically. For instance, this study focuses on epitomising the conceptual and analytical model to explore the effects of higher education and adult education within populations (popularisation of higher education) on economic growth (gross domestic product; GDP) and the poverty line. In addition, this study novelty combines both Mankiw-Romer-Weil model Solow model to investigate the effects of higher education and adult education within populations on economic growth and the poverty through OLS regression model and quantile model. For the practical aspect, this study practically uncovers the implicit significance of the popularisation of higher education for advocating UNESCO’s aim of developing inclusive and equitable quality education to achieve the fourth Sustainable Development Goal.

Limitations

This study had some limitations. Data could have been collected from a larger sample of OECD countries to explore the effect of population segments with higher education and adult education (popularisation of higher education) on economic growth (GDP) and the poverty line. In addition, a qualitative component could be included in future studies to uncover the cultural and historical contexts of the effect of popularising higher education on economic growth and poverty reduction at the local level. Future studies should also investigate the causal relationship between the popularisation of higher education and economic growth. Additional empirical data and advanced research methods can be used to enable a shift from correlation to causality.

In conclusion, this study examined the effect of the population segment with higher education and adult education (popularisation of higher education) on economic growth (GDP) and the poverty line using panel data from 38 countries. The population segment with higher education was found to have a significant positive impact on promoting GDP growth. An increase in the proportion of the working-age population segment that had completed higher education was evidently conducive to GDP growth. Popularisation of higher education was also found to play a positive role in the initial stage of economic and social development.

Data availability

The data of OECD country GDP is retrieved from https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=1W , The data of OECD country poverty line is retrieved from https://data.worldbank.org/indicator/SI.POV.DDAY?locations=1W&start=1984&view=chart , The data of OECD country Population with tertiary education 25–34-year-old is retrieved from https://data.oecd.org/eduatt/population-with-tertiary-education.htm#indicator-chart , The data of OECD country Percentage of 25–64-year old’s who have completed higher education (%) is retrieved from https://data.oecd.org/eduatt/adult-education-level.htm#indicator-chart , The datasets generated during and/or analysed during the current study are available in Harvard Dataverse https://doi.org/10.7910/DVN/TP43QS .

Adams, R (2013). Education: poverty and inequality blamed as UK sinks in adult literacy league: OECD survey flags up big problems for England: Post-16 education blamed for failure to address issue. The Guardian . (2013, October 9). London, England

Agasisti T, Longobardi S, Prete V, Russo F (2021) The relevance of educational poverty in europe: determinants and remedies. J Policy Model 43(3):692–709. https://doi.org/10.1016/j.jpolmod.2020.03.015

Article   Google Scholar  

Ainscow M (2020) Promoting inclusion and equity in education: lessons from international experiences. Nord J Stud Educ Policy 6(1):7–16

Balestra C, Ruiz N (2015) Scale-invariant measurement of inequality and welfare in ordinal achievements: an application to subjective well-being and education in OECD Countries. Soc Indic Res 123(2):479–500. https://doi.org/10.1007/s11205-014-0751-2

Bamberger, A, & Kim, MJ (2022) The OECD’s influence on national higher education policies: internationalisation in Israel and South Korea. Comp Educ 18. https://doi.org/10.1080/03050068.2022.2147635

Brand M (2021) The OECD poverty rate: lessons from the russian case. Glob Soc Policy 21(1):144–147

Camilla S. (2023) The design of upper secondary education across OECD countries: Managing choice, coherence and specialisation. OECD Education Working Papers. https://doi.org/10.1787/158101f0-en

Chakeredza S, Temu A, Saka J, Munthali D, Muir-Leresche K, Akinnifesi F, Ajayi O, Sileshi G (2008) Tailoring Tertiary Agricultural Education for Sustainable Development in Sub-Saharan Africa: Opportunities and Challenges. J Sci Res Essay 3(8):326–332

Google Scholar  

Chelli F, Ciommi M, Mariani F, Polinesi G, Recchioni MC, Lamonica GR, Salvati L (2022) A story of strengths and weaknesses in tertiary education: evaluating “Mobility” and “Opportunities” in OECD countries with composite indicators. Sustainability 14(24):16463. https://doi.org/10.3390/su142416463

Decancq, K (2017) Measuring multidimensional inequality in the OECD member countries with a distribution-sensitive better life index. Soc Indic Res 131(3):1057–1086. https://doi.org/10.1007/s11205-016-1289-2

Fang W, Farooq U, Liu Z, Lan J, Iram R (2022) Measuring energy efficiency financing: a way forward for reducing energy poverty through financial inclusion in OECD. Environ Sci Pollut Res 29(47):71923. https://doi.org/10.1007/s11356-022-20139-8

Garritzmann, JL (2016) The political economy of higher education finance: the politics of tuition fees and subsidies in OECD Countries, 1945–2015. Garritzmann. Germany, Berlin: Springer International Publishing

Gillian G, Lisa T, & Thomas W (2021) How are higher education systems in OECD countries resourced?: Evidence from an OECD Policy Survey.OCDE. https://doi.org/10.1787/0ac1fbad-en

Gong HJ, Hong JE (2021) Does postsecondary education attainment matter in community service engagement? Evidence from Across 18 OECD Countries. Educ Sci 11(3):1–17. https://doi.org/10.3390/educsci11030096

Article   MathSciNet   Google Scholar  

Granata, M (2022) The OECD and technical education in post-war Mediterranean Europe. Labor History. https://doi.org/10.1080/0023656X.2022.2057459

Habibi, F & Zabardast, MA (2020) Digitalization, education and economic growth: a comparative analysis of Middle East and OECD countries. Technol Soc 63. https://doi.org/10.1016/j.techsoc.2020.101370

Hoeller P, Joumard I, Koske I (2014) Reducing income inequality while boosting economic growth: can it be done? Evidence from OECD Countries. Singap Econ Rev 59(1):1–22

Jericho, G (2016) Australia didn’t have a ‘great recession’? Tell that to young people; an OECD report has found a rise in youth not in employment, education or training (Neets) since 2008. While historically the rate isn’t high, benefits are so low that youth are now more likely to be living in poverty. Guardian. London, England. https://link.gale.com/apps/doc/A463552813/AONE?u=unimelb&sid=bookmark-AONE&xid=701996a9

Julian LG (2018) The political economy of higher education finance. the politics of tuition fees and subsidies in OECD Countries, 1945–2015. Czech Sociol Rev 54(3):479–482

Jungblut J (2017) The political economy of higher education finance. The politics of tuition fees and subsidies in OECD countries, 1945–2015. Eur J High Educ 7(1):96–99. https://doi.org/10.1080/21568235.2017.1265789

Kalamova, M (2020) Resourcing higher education: challenges, choices and consequences. Higher Education Policy Team. Paris: OECD Publishing

Lamichhane, S, Egilmez, G, Gedik, R, Bhutta, MKS, & Erenay, B (2021) Benchmarking OECD countries’ sustainable development performance: a goal-specific principal component analysis approach. J Clea Prod 287. https://doi.org/10.1016/j.jclepro.2020.125040

Ledger, S, Thier, M, Bailey, L, & Pitts, C (2019) OECD’s approach to measuring global competency: powerful voices shaping education. Teachers College Record, 121(8):1–40

Li, J & Xue. E (2021) Returnee faculty responses to internationalizing “Academic Ecology” for Creating World-class Universities in China’ Elite Universities. Higher Education. 81(5), 1063–1078

Li, J, & Xue. E, Liu, C, Li, X (2023) Integrated macro and micro analyses of student burden reduction policies in China: call for a collaborative “family–school–society” model. Humanities & Social Sciences Communications. 10, 184 (2023). https://doi.org/10.1057/s41599-023-01695-x

Liu, L (2017) Exploring the relationship between education economy and individual civic attitudes: a cross-national analysis in England, Spain, Sweden, Poland and Chinese Taipei

Lucas R (1988) On the mechanics of economic development. J. Monetary Econ 22(1):342

Mathias B (2023). The assessment of students’ creative and critical thinking skills in higher education across OECD countries: a review of policies and related practices. OECD Education Working Papers. https://doi.org/10.1787/35dbd439-en

Megyesiova, S, & Lieskovska, V (2018) Analysis of the sustainable development indicators in the OECD Countries. Sustainability 10(12). https://doi.org/10.3390/su10124554

Mitic RR (2018) The political economy of higher education finance: the politics of tuition fees and subsidies in OECD Countries, 1945-2015. Rev High Educ 41(3):484–487

OECD (2022) Education at a Glance 2022: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/3197152b-en

Özdoğan Özbal E (2021) Dynamic effects of higher education expenditures on human capital and economic growth: an evaluation of OECD countries. Policy Rev High Educ 5(2):174–196. https://doi.org/10.1080/23322969.2021.1893125

Pinheiro R, Pillay P (2016) Higher education and economic development in the OECD: policy lessons for other countries and regions. J High Educ Policy Manag 38(2):150

Romer M (1990) Endogenous technological change. J Political Econ 98(5):S71–S102

Rowe E (2019) Capitalism without capital: the intangible economy of education reform. Discourse 40(2):271

Sahnoun M, Abdennadher C (2022) Returns to investment in education in the OECD Countries: does governance quality matter? J Knowldege Econ 13(3):1819–1842. https://doi.org/10.1007/s13132-021-00783-0

Samo V. (2022). A snapshot of equity and inclusion in OECD education systems: findings from the Strength through Diversity Policy Survey. OECD Eduction Working Papers. https://doi.org/10.1787/801dd29b-en

Schultz (1961) Investment in human capital. Am Econ Rev 51(1):1–17

Solow RM (1957) Technical change and the aggregate production function. Rev Econ Stat 39(3):312–320

Zapp M (2022) Revisiting the global knowledge economy: the worldwide expansion of research and development personnel, 1980–2015. Minerva 60(2):181–208. https://doi.org/10.1007/s11024-021-09455-4

Article   PubMed   PubMed Central   Google Scholar  

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Acknowledgements

This study is funded by 2021 National Social Science Foundation of Higher Education Ideological and Political Course research (Key project) Ideological and Political Education System Construction System Mechanism Research in New Era (No.: 21VSZ004).

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Institute of International and Comparative Education, Beijing Normal University, Beijing, 100875, China

China Institute of Education Policy, Faculty of Education, Beijing Normal University, Beijing, 100875, China

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Li, J., Xue, E., Wei, Y. et al. How popularising higher education affects economic growth and poverty alleviation: empirical evidence from 38 countries. Humanit Soc Sci Commun 11 , 520 (2024). https://doi.org/10.1057/s41599-024-03013-5

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1 What is Action Research for Classroom Teachers?

ESSENTIAL QUESTIONS

• What is the nature of action research?
• How does action research develop in the classroom?
• What models of action research work best for your classroom?
• What are the epistemological, ontological, theoretical underpinnings of action research?

Educational research provides a vast landscape of knowledge on topics related to teaching and learning, curriculum and assessment, students’ cognitive and affective needs, cultural and socio-economic factors of schools, and many other factors considered viable to improving schools. Educational stakeholders rely on research to make informed decisions that ultimately affect the quality of schooling for their students. Accordingly, the purpose of educational research is to engage in disciplined inquiry to generate knowledge on topics significant to the students, teachers, administrators, schools, and other educational stakeholders. Just as the topics of educational research vary, so do the approaches to conducting educational research in the classroom. Your approach to research will be shaped by your context, your professional identity, and paradigm (set of beliefs and assumptions that guide your inquiry). These will all be key factors in how you generate knowledge related to your work as an educator.

Action research is an approach to educational research that is commonly used by educational practitioners and professionals to examine, and ultimately improve, their pedagogy and practice. In this way, action research represents an extension of the reflection and critical self-reflection that an educator employs on a daily basis in their classroom. When students are actively engaged in learning, the classroom can be dynamic and uncertain, demanding the constant attention of the educator. Considering these demands, educators are often only able to engage in reflection that is fleeting, and for the purpose of accommodation, modification, or formative assessment. Action research offers one path to more deliberate, substantial, and critical reflection that can be documented and analyzed to improve an educator’s practice.

Purpose of Action Research

As one of many approaches to educational research, it is important to distinguish the potential purposes of action research in the classroom. This book focuses on action research as a method to enable and support educators in pursuing effective pedagogical practices by transforming the quality of teaching decisions and actions, to subsequently enhance student engagement and learning. Being mindful of this purpose, the following aspects of action research are important to consider as you contemplate and engage with action research methodology in your classroom:

• Action research is a process for improving educational practice. Its methods involve action, evaluation, and reflection. It is a process to gather evidence to implement change in practices.
• Action research is participative and collaborative. It is undertaken by individuals with a common purpose.
• Action research is situation and context-based.
• Action research develops reflection practices based on the interpretations made by participants.
• Knowledge is created through action and application.
• Action research can be based in problem-solving, if the solution to the problem results in the improvement of practice.
• Action research is iterative; plans are created, implemented, revised, then implemented, lending itself to an ongoing process of reflection and revision.
• In action research, findings emerge as action develops and takes place; however, they are not conclusive or absolute, but ongoing (Koshy, 2010, pgs. 1-2).

In thinking about the purpose of action research, it is helpful to situate action research as a distinct paradigm of educational research. I like to think about action research as part of the larger concept of living knowledge. Living knowledge has been characterized as “a quest for life, to understand life and to create… knowledge which is valid for the people with whom I work and for myself” (Swantz, in Reason & Bradbury, 2001, pg. 1). Why should educators care about living knowledge as part of educational research? As mentioned above, action research is meant “to produce practical knowledge that is useful to people in the everyday conduct of their lives and to see that action research is about working towards practical outcomes” (Koshy, 2010, pg. 2). However, it is also about:

creating new forms of understanding, since action without reflection and understanding is blind, just as theory without action is meaningless. The participatory nature of action research makes it only possible with, for and by persons and communities, ideally involving all stakeholders both in the questioning and sense making that informs the research, and in the action, which is its focus. (Reason & Bradbury, 2001, pg. 2)

In an effort to further situate action research as living knowledge, Jean McNiff reminds us that “there is no such ‘thing’ as ‘action research’” (2013, pg. 24). In other words, action research is not static or finished, it defines itself as it proceeds. McNiff’s reminder characterizes action research as action-oriented, and a process that individuals go through to make their learning public to explain how it informs their practice. Action research does not derive its meaning from an abstract idea, or a self-contained discovery – action research’s meaning stems from the way educators negotiate the problems and successes of living and working in the classroom, school, and community.

While we can debate the idea of action research, there are people who are action researchers, and they use the idea of action research to develop principles and theories to guide their practice. Action research, then, refers to an organization of principles that guide action researchers as they act on shared beliefs, commitments, and expectations in their inquiry.

Reflection and the Process of Action Research

When an individual engages in reflection on their actions or experiences, it is typically for the purpose of better understanding those experiences, or the consequences of those actions to improve related action and experiences in the future. Reflection in this way develops knowledge around these actions and experiences to help us better regulate those actions in the future. The reflective process generates new knowledge regularly for classroom teachers and informs their classroom actions.

Unfortunately, the knowledge generated by educators through the reflective process is not always prioritized among the other sources of knowledge educators are expected to utilize in the classroom. Educators are expected to draw upon formal types of knowledge, such as textbooks, content standards, teaching standards, district curriculum and behavioral programs, etc., to gain new knowledge and make decisions in the classroom. While these forms of knowledge are important, the reflective knowledge that educators generate through their pedagogy is the amalgamation of these types of knowledge enacted in the classroom. Therefore, reflective knowledge is uniquely developed based on the action and implementation of an educator’s pedagogy in the classroom. Action research offers a way to formalize the knowledge generated by educators so that it can be utilized and disseminated throughout the teaching profession.

Research is concerned with the generation of knowledge, and typically creating knowledge related to a concept, idea, phenomenon, or topic. Action research generates knowledge around inquiry in practical educational contexts. Action research allows educators to learn through their actions with the purpose of developing personally or professionally. Due to its participatory nature, the process of action research is also distinct in educational research. There are many models for how the action research process takes shape. I will share a few of those here. Each model utilizes the following processes to some extent:

• Plan a change;
• Take action to enact the change;
• Observe the process and consequences of the change;
• Reflect on the process and consequences;
• Act, observe, & reflect again and so on.

Figure 1.1 Basic action research cycle

There are many other models that supplement the basic process of action research with other aspects of the research process to consider. For example, figure 1.2 illustrates a spiral model of action research proposed by Kemmis and McTaggart (2004). The spiral model emphasizes the cyclical process that moves beyond the initial plan for change. The spiral model also emphasizes revisiting the initial plan and revising based on the initial cycle of research:

Figure 1.2 Interpretation of action research spiral, Kemmis and McTaggart (2004, p. 595)

Other models of action research reorganize the process to emphasize the distinct ways knowledge takes shape in the reflection process. O’Leary’s (2004, p. 141) model, for example, recognizes that the research may take shape in the classroom as knowledge emerges from the teacher’s observations. O’Leary highlights the need for action research to be focused on situational understanding and implementation of action, initiated organically from real-time issues:

Figure 1.3 Interpretation of O’Leary’s cycles of research, O’Leary (2000, p. 141)

Lastly, Macintyre’s (2000, p. 1) model, offers a different characterization of the action research process. Macintyre emphasizes a messier process of research with the initial reflections and conclusions as the benchmarks for guiding the research process. Macintyre emphasizes the flexibility in planning, acting, and observing stages to allow the process to be naturalistic. Our interpretation of Macintyre process is below:

Figure 1.4 Interpretation of the action research cycle, Macintyre (2000, p. 1)

We believe it is important to prioritize the flexibility of the process, and encourage you to only use these models as basic guides for your process. Your process may look similar, or you may diverge from these models as you better understand your students, context, and data.

Definitions of Action Research and Examples

At this point, it may be helpful for readers to have a working definition of action research and some examples to illustrate the methodology in the classroom. Bassey (1998, p. 93) offers a very practical definition and describes “action research as an inquiry which is carried out in order to understand, to evaluate and then to change, in order to improve educational practice.” Cohen and Manion (1994, p. 192) situate action research differently, and describe action research as emergent, writing:

essentially an on-the-spot procedure designed to deal with a concrete problem located in an immediate situation. This means that ideally, the step-by-step process is constantly monitored over varying periods of time and by a variety of mechanisms (questionnaires, diaries, interviews and case studies, for example) so that the ensuing feedback may be translated into modifications, adjustment, directional changes, redefinitions, as necessary, so as to bring about lasting benefit to the ongoing process itself rather than to some future occasion.

Lastly, Koshy (2010, p. 9) describes action research as:

a constructive inquiry, during which the researcher constructs his or her knowledge of specific issues through planning, acting, evaluating, refining and learning from the experience. It is a continuous learning process in which the researcher learns and also shares the newly generated knowledge with those who may benefit from it.

These definitions highlight the distinct features of action research and emphasize the purposeful intent of action researchers to improve, refine, reform, and problem-solve issues in their educational context. To better understand the distinctness of action research, these are some examples of action research topics:

Examples of Action Research Topics

• Flexible seating in 4th grade classroom to increase effective collaborative learning.
• Structured homework protocols for increasing student achievement.
• Developing a system of formative feedback for 8th grade writing.
• Using music to stimulate creative writing.
• Weekly brown bag lunch sessions to improve responses to PD from staff.
• Using exercise balls as chairs for better classroom management.

Action Research in Theory

Action research-based inquiry in educational contexts and classrooms involves distinct participants – students, teachers, and other educational stakeholders within the system. All of these participants are engaged in activities to benefit the students, and subsequently society as a whole. Action research contributes to these activities and potentially enhances the participants’ roles in the education system. Participants’ roles are enhanced based on two underlying principles:

• communities, schools, and classrooms are sites of socially mediated actions, and action research provides a greater understanding of self and new knowledge of how to negotiate these socially mediated environments;
• communities, schools, and classrooms are part of social systems in which humans interact with many cultural tools, and action research provides a basis to construct and analyze these interactions.

In our quest for knowledge and understanding, we have consistently analyzed human experience over time and have distinguished between types of reality. Humans have constantly sought “facts” and “truth” about reality that can be empirically demonstrated or observed.

Social systems are based on beliefs, and generally, beliefs about what will benefit the greatest amount of people in that society. Beliefs, and more specifically the rationale or support for beliefs, are not always easy to demonstrate or observe as part of our reality. Take the example of an English Language Arts teacher who prioritizes argumentative writing in her class. She believes that argumentative writing demonstrates the mechanics of writing best among types of writing, while also providing students a skill they will need as citizens and professionals. While we can observe the students writing, and we can assess their ability to develop a written argument, it is difficult to observe the students’ understanding of argumentative writing and its purpose in their future. This relates to the teacher’s beliefs about argumentative writing; we cannot observe the real value of the teaching of argumentative writing. The teacher’s rationale and beliefs about teaching argumentative writing are bound to the social system and the skills their students will need to be active parts of that system. Therefore, our goal through action research is to demonstrate the best ways to teach argumentative writing to help all participants understand its value as part of a social system.

The knowledge that is conveyed in a classroom is bound to, and justified by, a social system. A postmodernist approach to understanding our world seeks knowledge within a social system, which is directly opposed to the empirical or positivist approach which demands evidence based on logic or science as rationale for beliefs. Action research does not rely on a positivist viewpoint to develop evidence and conclusions as part of the research process. Action research offers a postmodernist stance to epistemology (theory of knowledge) and supports developing questions and new inquiries during the research process. In this way action research is an emergent process that allows beliefs and decisions to be negotiated as reality and meaning are being constructed in the socially mediated space of the classroom.

Theorizing Action Research for the Classroom

All research, at its core, is for the purpose of generating new knowledge and contributing to the knowledge base of educational research. Action researchers in the classroom want to explore methods of improving their pedagogy and practice. The starting place of their inquiry stems from their pedagogy and practice, so by nature the knowledge created from their inquiry is often contextually specific to their classroom, school, or community. Therefore, we should examine the theoretical underpinnings of action research for the classroom. It is important to connect action research conceptually to experience; for example, Levin and Greenwood (2001, p. 105) make these connections:

• Action research is context bound and addresses real life problems.
• Action research is inquiry where participants and researchers cogenerate knowledge through collaborative communicative processes in which all participants’ contributions are taken seriously.
• The meanings constructed in the inquiry process lead to social action or these reflections and action lead to the construction of new meanings.
• The credibility/validity of action research knowledge is measured according to whether the actions that arise from it solve problems (workability) and increase participants’ control over their own situation.

Educators who engage in action research will generate new knowledge and beliefs based on their experiences in the classroom. Let us emphasize that these are all important to you and your work, as both an educator and researcher. It is these experiences, beliefs, and theories that are often discounted when more official forms of knowledge (e.g., textbooks, curriculum standards, districts standards) are prioritized. These beliefs and theories based on experiences should be valued and explored further, and this is one of the primary purposes of action research in the classroom. These beliefs and theories should be valued because they were meaningful aspects of knowledge constructed from teachers’ experiences. Developing meaning and knowledge in this way forms the basis of constructivist ideology, just as teachers often try to get their students to construct their own meanings and understandings when experiencing new ideas.  

Classroom Teachers Constructing their Own Knowledge

Most of you are probably at least minimally familiar with constructivism, or the process of constructing knowledge. However, what is constructivism precisely, for the purposes of action research? Many scholars have theorized constructivism and have identified two key attributes (Koshy, 2010; von Glasersfeld, 1987):

• Knowledge is not passively received, but actively developed through an individual’s cognition;
• Human cognition is adaptive and finds purpose in organizing the new experiences of the world, instead of settling for absolute or objective truth.

Considering these two attributes, constructivism is distinct from conventional knowledge formation because people can develop a theory of knowledge that orders and organizes the world based on their experiences, instead of an objective or neutral reality. When individuals construct knowledge, there are interactions between an individual and their environment where communication, negotiation and meaning-making are collectively developing knowledge. For most educators, constructivism may be a natural inclination of their pedagogy. Action researchers have a similar relationship to constructivism because they are actively engaged in a process of constructing knowledge. However, their constructions may be more formal and based on the data they collect in the research process. Action researchers also are engaged in the meaning making process, making interpretations from their data. These aspects of the action research process situate them in the constructivist ideology. Just like constructivist educators, action researchers’ constructions of knowledge will be affected by their individual and professional ideas and values, as well as the ecological context in which they work (Biesta & Tedder, 2006). The relations between constructivist inquiry and action research is important, as Lincoln (2001, p. 130) states:

much of the epistemological, ontological, and axiological belief systems are the same or similar, and methodologically, constructivists and action researchers work in similar ways, relying on qualitative methods in face-to-face work, while buttressing information, data and background with quantitative method work when necessary or useful.

While there are many links between action research and educators in the classroom, constructivism offers the most familiar and practical threads to bind the beliefs of educators and action researchers.  

Epistemology, Ontology, and Action Research

It is also important for educators to consider the philosophical stances related to action research to better situate it with their beliefs and reality. When researchers make decisions about the methodology they intend to use, they will consider their ontological and epistemological stances. It is vital that researchers clearly distinguish their philosophical stances and understand the implications of their stance in the research process, especially when collecting and analyzing their data. In what follows, we will discuss ontological and epistemological stances in relation to action research methodology.

Ontology, or the theory of being, is concerned with the claims or assumptions we make about ourselves within our social reality – what do we think exists, what does it look like, what entities are involved and how do these entities interact with each other (Blaikie, 2007). In relation to the discussion of constructivism, generally action researchers would consider their educational reality as socially constructed. Social construction of reality happens when individuals interact in a social system. Meaningful construction of concepts and representations of reality develop through an individual’s interpretations of others’ actions. These interpretations become agreed upon by members of a social system and become part of social fabric, reproduced as knowledge and beliefs to develop assumptions about reality. Researchers develop meaningful constructions based on their experiences and through communication. Educators as action researchers will be examining the socially constructed reality of schools. In the United States, many of our concepts, knowledge, and beliefs about schooling have been socially constructed over the last hundred years. For example, a group of teachers may look at why fewer female students enroll in upper-level science courses at their school. This question deals directly with the social construction of gender and specifically what careers females have been conditioned to pursue. We know this is a social construction in some school social systems because in other parts of the world, or even the United States, there are schools that have more females enrolled in upper level science courses than male students. Therefore, the educators conducting the research have to recognize the socially constructed reality of their school and consider this reality throughout the research process. Action researchers will use methods of data collection that support their ontological stance and clarify their theoretical stance throughout the research process.

Koshy (2010, p. 23-24) offers another example of addressing the ontological challenges in the classroom:

A teacher who was concerned with increasing her pupils’ motivation and enthusiasm for learning decided to introduce learning diaries which the children could take home. They were invited to record their reactions to the day’s lessons and what they had learnt. The teacher reported in her field diary that the learning diaries stimulated the children’s interest in her lessons, increased their capacity to learn, and generally improved their level of participation in lessons. The challenge for the teacher here is in the analysis and interpretation of the multiplicity of factors accompanying the use of diaries. The diaries were taken home so the entries may have been influenced by discussions with parents. Another possibility is that children felt the need to please their teacher. Another possible influence was that their increased motivation was as a result of the difference in style of teaching which included more discussions in the classroom based on the entries in the dairies.

Here you can see the challenge for the action researcher is working in a social context with multiple factors, values, and experiences that were outside of the teacher’s control. The teacher was only responsible for introducing the diaries as a new style of learning. The students’ engagement and interactions with this new style of learning were all based upon their socially constructed notions of learning inside and outside of the classroom. A researcher with a positivist ontological stance would not consider these factors, and instead might simply conclude that the dairies increased motivation and interest in the topic, as a result of introducing the diaries as a learning strategy.

Epistemology, or the theory of knowledge, signifies a philosophical view of what counts as knowledge – it justifies what is possible to be known and what criteria distinguishes knowledge from beliefs (Blaikie, 1993). Positivist researchers, for example, consider knowledge to be certain and discovered through scientific processes. Action researchers collect data that is more subjective and examine personal experience, insights, and beliefs.

Action researchers utilize interpretation as a means for knowledge creation. Action researchers have many epistemologies to choose from as means of situating the types of knowledge they will generate by interpreting the data from their research. For example, Koro-Ljungberg et al., (2009) identified several common epistemologies in their article that examined epistemological awareness in qualitative educational research, such as: objectivism, subjectivism, constructionism, contextualism, social epistemology, feminist epistemology, idealism, naturalized epistemology, externalism, relativism, skepticism, and pluralism. All of these epistemological stances have implications for the research process, especially data collection and analysis. Please see the table on pages 689-90, linked below for a sketch of these potential implications:

Again, Koshy (2010, p. 24) provides an excellent example to illustrate the epistemological challenges within action research:

A teacher of 11-year-old children decided to carry out an action research project which involved a change in style in teaching mathematics. Instead of giving children mathematical tasks displaying the subject as abstract principles, she made links with other subjects which she believed would encourage children to see mathematics as a discipline that could improve their understanding of the environment and historic events. At the conclusion of the project, the teacher reported that applicable mathematics generated greater enthusiasm and understanding of the subject.

The educator/researcher engaged in action research-based inquiry to improve an aspect of her pedagogy. She generated knowledge that indicated she had improved her students’ understanding of mathematics by integrating it with other subjects – specifically in the social and ecological context of her classroom, school, and community. She valued constructivism and students generating their own understanding of mathematics based on related topics in other subjects. Action researchers working in a social context do not generate certain knowledge, but knowledge that emerges and can be observed and researched again, building upon their knowledge each time.

Researcher Positionality in Action Research

In this first chapter, we have discussed a lot about the role of experiences in sparking the research process in the classroom. Your experiences as an educator will shape how you approach action research in your classroom. Your experiences as a person in general will also shape how you create knowledge from your research process. In particular, your experiences will shape how you make meaning from your findings. It is important to be clear about your experiences when developing your methodology too. This is referred to as researcher positionality. Maher and Tetreault (1993, p. 118) define positionality as:

Gender, race, class, and other aspects of our identities are markers of relational positions rather than essential qualities. Knowledge is valid when it includes an acknowledgment of the knower’s specific position in any context, because changing contextual and relational factors are crucial for defining identities and our knowledge in any given situation.

By presenting your positionality in the research process, you are signifying the type of socially constructed, and other types of, knowledge you will be using to make sense of the data. As Maher and Tetreault explain, this increases the trustworthiness of your conclusions about the data. This would not be possible with a positivist ontology. We will discuss positionality more in chapter 6, but we wanted to connect it to the overall theoretical underpinnings of action research.

Advantages of Engaging in Action Research in the Classroom

In the following chapters, we will discuss how action research takes shape in your classroom, and we wanted to briefly summarize the key advantages to action research methodology over other types of research methodology. As Koshy (2010, p. 25) notes, action research provides useful methodology for school and classroom research because:

Advantages of Action Research for the Classroom

• research can be set within a specific context or situation;
• researchers can be participants – they don’t have to be distant and detached from the situation;
• it involves continuous evaluation and modifications can be made easily as the project progresses;
• there are opportunities for theory to emerge from the research rather than always follow a previously formulated theory;
• the study can lead to open-ended outcomes;
• through action research, a researcher can bring a story to life.

Action Research Copyright © by J. Spencer Clark; Suzanne Porath; Julie Thiele; and Morgan Jobe is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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• Research article
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• Published: 06 February 2017

Blended learning effectiveness: the relationship between student characteristics, design features and outcomes

• Mugenyi Justice Kintu   ORCID: orcid.org/0000-0002-4500-1168 1 , 2 ,
• Chang Zhu 2 &
• Edmond Kagambe 1  

International Journal of Educational Technology in Higher Education volume  14 , Article number:  7 ( 2017 ) Cite this article

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This paper investigates the effectiveness of a blended learning environment through analyzing the relationship between student characteristics/background, design features and learning outcomes. It is aimed at determining the significant predictors of blended learning effectiveness taking student characteristics/background and design features as independent variables and learning outcomes as dependent variables. A survey was administered to 238 respondents to gather data on student characteristics/background, design features and learning outcomes. The final semester evaluation results were used as a measure for performance as an outcome. We applied the online self regulatory learning questionnaire for data on learner self regulation, the intrinsic motivation inventory for data on intrinsic motivation and other self-developed instruments for measuring the other constructs. Multiple regression analysis results showed that blended learning design features (technology quality, online tools and face-to-face support) and student characteristics (attitudes and self-regulation) predicted student satisfaction as an outcome. The results indicate that some of the student characteristics/backgrounds and design features are significant predictors for student learning outcomes in blended learning.

Introduction

The teaching and learning environment is embracing a number of innovations and some of these involve the use of technology through blended learning. This innovative pedagogical approach has been embraced rapidly though it goes through a process. The introduction of blended learning (combination of face-to-face and online teaching and learning) initiatives is part of these innovations but its uptake, especially in the developing world faces challenges for it to be an effective innovation in teaching and learning. Blended learning effectiveness has quite a number of underlying factors that pose challenges. One big challenge is about how users can successfully use the technology and ensuring participants’ commitment given the individual learner characteristics and encounters with technology (Hofmann, 2014 ). Hofmann adds that users getting into difficulties with technology may result into abandoning the learning and eventual failure of technological applications. In a report by Oxford Group ( 2013 ), some learners (16%) had negative attitudes to blended learning while 26% were concerned that learners would not complete study in blended learning. Learners are important partners in any learning process and therefore, their backgrounds and characteristics affect their ability to effectively carry on with learning and being in blended learning, the design tools to be used may impinge on the effectiveness in their learning.

This study tackles blended learning effectiveness which has been investigated in previous studies considering grades, course completion, retention and graduation rates but no studies regarding effectiveness in view of learner characteristics/background, design features and outcomes have been done in the Ugandan university context. No studies have also been done on how the characteristics of learners and design features are predictors of outcomes in the context of a planning evaluation research (Guskey, 2000 ) to establish the effectiveness of blended learning. Guskey ( 2000 ) noted that planning evaluation fits in well since it occurs before the implementation of any innovation as well as allowing planners to determine the needs, considering participant characteristics, analyzing contextual matters and gathering baseline information. This study is done in the context of a plan to undertake innovative pedagogy involving use of a learning management system (moodle) for the first time in teaching and learning in a Ugandan university. The learner characteristics/backgrounds being investigated for blended learning effectiveness include self-regulation, computer competence, workload management, social and family support, attitude to blended learning, gender and age. We investigate the blended learning design features of learner interactions, face-to-face support, learning management system tools and technology quality while the outcomes considered include satisfaction, performance, intrinsic motivation and knowledge construction. Establishing the significant predictors of outcomes in blended learning will help to inform planners of such learning environments in order to put in place necessary groundwork preparations for designing blended learning as an innovative pedagogical approach.

Kenney and Newcombe ( 2011 ) did their comparison to establish effectiveness in view of grades and found that blended learning had higher average score than the non-blended learning environment. Garrison and Kanuka ( 2004 ) examined the transformative potential of blended learning and reported an increase in course completion rates, improved retention and increased student satisfaction. Comparisons between blended learning environments have been done to establish the disparity between academic achievement, grade dispersions and gender performance differences and no significant differences were found between the groups (Demirkol & Kazu, 2014 ).

However, blended learning effectiveness may be dependent on many other factors and among them student characteristics, design features and learning outcomes. Research shows that the failure of learners to continue their online education in some cases has been due to family support or increased workload leading to learner dropout (Park & Choi, 2009 ) as well as little time for study. Additionally, it is dependent on learner interactions with instructors since failure to continue with online learning is attributed to this. In Greer, Hudson & Paugh’s study as cited in Park and Choi ( 2009 ), family and peer support for learners is important for success in online and face-to-face learning. Support is needed for learners from all areas in web-based courses and this may be from family, friends, co-workers as well as peers in class. Greer, Hudson and Paugh further noted that peer encouragement assisted new learners in computer use and applications. The authors also show that learners need time budgeting, appropriate technology tools and support from friends and family in web-based courses. Peer support is required by learners who have no or little knowledge of technology, especially computers, to help them overcome fears. Park and Choi, ( 2009 ) showed that organizational support significantly predicts learners’ stay and success in online courses because employers at times are willing to reduce learners’ workload during study as well as supervisors showing that they are interested in job-related learning for employees to advance and improve their skills.

The study by Kintu and Zhu ( 2016 ) investigated the possibility of blended learning in a Ugandan University and examined whether student characteristics (such as self-regulation, attitudes towards blended learning, computer competence) and student background (such as family support, social support and management of workload) were significant factors in learner outcomes (such as motivation, satisfaction, knowledge construction and performance). The characteristics and background factors were studied along with blended learning design features such as technology quality, learner interactions, and Moodle with its tools and resources. The findings from that study indicated that learner attitudes towards blended learning were significant factors to learner satisfaction and motivation while workload management was a significant factor to learner satisfaction and knowledge construction. Among the blended learning design features, only learner interaction was a significant factor to learner satisfaction and knowledge construction.

The focus of the present study is on examining the effectiveness of blended learning taking into consideration learner characteristics/background, blended learning design elements and learning outcomes and how the former are significant predictors of blended learning effectiveness.

Studies like that of Morris and Lim ( 2009 ) have investigated learner and instructional factors influencing learning outcomes in blended learning. They however do not deal with such variables in the contexts of blended learning design as an aspect of innovative pedagogy involving the use of technology in education. Apart from the learner variables such as gender, age, experience, study time as tackled before, this study considers social and background aspects of the learners such as family and social support, self-regulation, attitudes towards blended learning and management of workload to find out their relationship to blended learning effectiveness. Identifying the various types of learner variables with regard to their relationship to blended learning effectiveness is important in this study as we embark on innovative pedagogy with technology in teaching and learning.

Literature review

This review presents research about blended learning effectiveness from the perspective of learner characteristics/background, design features and learning outcomes. It also gives the factors that are considered to be significant for blended learning effectiveness. The selected elements are as a result of the researcher’s experiences at a Ugandan university where student learning faces challenges with regard to learner characteristics and blended learning features in adopting the use of technology in teaching and learning. We have made use of Loukis, Georgiou, and Pazalo ( 2007 ) value flow model for evaluating an e-learning and blended learning service specifically considering the effectiveness evaluation layer. This evaluates the extent of an e-learning system usage and the educational effectiveness. In addition, studies by Leidner, Jarvenpaa, Dillon and Gunawardena as cited in Selim ( 2007 ) have noted three main factors that affect e-learning and blended learning effectiveness as instructor characteristics, technology and student characteristics. Heinich, Molenda, Russell, and Smaldino ( 2001 ) showed the need for examining learner characteristics for effective instructional technology use and showed that user characteristics do impact on behavioral intention to use technology. Research has dealt with learner characteristics that contribute to learner performance outcomes. They have dealt with emotional intelligence, resilience, personality type and success in an online learning context (Berenson, Boyles, & Weaver, 2008 ). Dealing with the characteristics identified in this study will give another dimension, especially for blended learning in learning environment designs and add to specific debate on learning using technology. Lin and Vassar, ( 2009 ) indicated that learner success is dependent on ability to cope with technical difficulty as well as technical skills in computer operations and internet navigation. This justifies our approach in dealing with the design features of blended learning in this study.

Learner characteristics/background and blended learning effectiveness

Studies indicate that student characteristics such as gender play significant roles in academic achievement (Oxford Group, 2013 ), but no study examines performance of male and female as an important factor in blended learning effectiveness. It has again been noted that the success of e- and blended learning is highly dependent on experience in internet and computer applications (Picciano & Seaman, 2007 ). Rigorous discovery of such competences can finally lead to a confirmation of high possibilities of establishing blended learning. Research agrees that the success of e-learning and blended learning can largely depend on students as well as teachers gaining confidence and capability to participate in blended learning (Hadad, 2007 ). Shraim and Khlaif ( 2010 ) note in their research that 75% of students and 72% of teachers were lacking in skills to utilize ICT based learning components due to insufficient skills and experience in computer and internet applications and this may lead to failure in e-learning and blended learning. It is therefore pertinent that since the use of blended learning applies high usage of computers, computer competence is necessary (Abubakar & Adetimirin, 2015 ) to avoid failure in applying technology in education for learning effectiveness. Rovai, ( 2003 ) noted that learners’ computer literacy and time management are crucial in distance learning contexts and concluded that such factors are meaningful in online classes. This is supported by Selim ( 2007 ) that learners need to posses time management skills and computer skills necessary for effectiveness in e- learning and blended learning. Self-regulatory skills of time management lead to better performance and learners’ ability to structure the physical learning environment leads to efficiency in e-learning and blended learning environments. Learners need to seek helpful assistance from peers and teachers through chats, email and face-to-face meetings for effectiveness (Lynch & Dembo, 2004 ). Factors such as learners’ hours of employment and family responsibilities are known to impede learners’ process of learning, blended learning inclusive (Cohen, Stage, Hammack, & Marcus, 2012 ). It was also noted that a common factor in failure and learner drop-out is the time conflict which is compounded by issues of family , employment status as well as management support (Packham, Jones, Miller, & Thomas, 2004 ). A study by Thompson ( 2004 ) shows that work, family, insufficient time and study load made learners withdraw from online courses.

Learner attitudes to blended learning can result in its effectiveness and these shape behavioral intentions which usually lead to persistence in a learning environment, blended inclusive. Selim, ( 2007 ) noted that the learners’ attitude towards e-learning and blended learning are success factors for these learning environments. Learner performance by age and gender in e-learning and blended learning has been found to indicate no significant differences between male and female learners and different age groups (i.e. young, middle-aged and old above 45 years) (Coldwell, Craig, Paterson, & Mustard, 2008 ). This implies that the potential for blended learning to be effective exists and is unhampered by gender or age differences.

Blended learning design features

The design features under study here include interactions, technology with its quality, face-to-face support and learning management system tools and resources.

Research shows that absence of learner interaction causes failure and eventual drop-out in online courses (Willging & Johnson, 2009 ) and the lack of learner connectedness was noted as an internal factor leading to learner drop-out in online courses (Zielinski, 2000 ). It was also noted that learners may not continue in e- and blended learning if they are unable to make friends thereby being disconnected and developing feelings of isolation during their blended learning experiences (Willging & Johnson, 2009). Learners’ Interactions with teachers and peers can make blended learning effective as its absence makes learners withdraw (Astleitner, 2000 ). Loukis, Georgious and Pazalo (2007) noted that learners’ measuring of a system’s quality, reliability and ease of use leads to learning efficiency and can be so in blended learning. Learner success in blended learning may substantially be affected by system functionality (Pituch & Lee, 2006 ) and may lead to failure of such learning initiatives (Shrain, 2012 ). It is therefore important to examine technology quality for ensuring learning effectiveness in blended learning. Tselios, Daskalakis, and Papadopoulou ( 2011 ) investigated learner perceptions after a learning management system use and found out that the actual system use determines the usefulness among users. It is again noted that a system with poor response time cannot be taken to be useful for e-learning and blended learning especially in cases of limited bandwidth (Anderson, 2004 ). In this study, we investigate the use of Moodle and its tools as a function of potential effectiveness of blended learning.

The quality of learning management system content for learners can be a predictor of good performance in e-and blended learning environments and can lead to learner satisfaction. On the whole, poor quality technology yields no satisfaction by users and therefore the quality of technology significantly affects satisfaction (Piccoli, Ahmad, & Ives, 2001 ). Continued navigation through a learning management system increases use and is an indicator of success in blended learning (Delone & McLean, 2003 ). The efficient use of learning management system and its tools improves learning outcomes in e-learning and blended learning environments.

It is noted that learner satisfaction with a learning management system can be an antecedent factor for blended learning effectiveness. Goyal and Tambe ( 2015 ) noted that learners showed an appreciation to Moodle’s contribution in their learning. They showed positivity with it as it improved their understanding of course material (Ahmad & Al-Khanjari, 2011 ). The study by Goyal and Tambe ( 2015 ) used descriptive statistics to indicate improved learning by use of uploaded syllabus and session plans on Moodle. Improved learning is also noted through sharing study material, submitting assignments and using the calendar. Learners in the study found Moodle to be an effective educational tool.

In blended learning set ups, face-to-face experiences form part of the blend and learner positive attitudes to such sessions could mean blended learning effectiveness. A study by Marriot, Marriot, and Selwyn ( 2004 ) showed learners expressing their preference for face-to-face due to its facilitation of social interaction and communication skills acquired from classroom environment. Their preference for the online session was only in as far as it complemented the traditional face-to-face learning. Learners in a study by Osgerby ( 2013 ) had positive perceptions of blended learning but preferred face-to-face with its step-by-stem instruction. Beard, Harper and Riley ( 2004 ) shows that some learners are successful while in a personal interaction with teachers and peers thus prefer face-to-face in the blend. Beard however dealt with a comparison between online and on-campus learning while our study combines both, singling out the face-to-face part of the blend. The advantage found by Beard is all the same relevant here because learners in blended learning express attitude to both online and face-to-face for an effective blend. Researchers indicate that teacher presence in face-to-face sessions lessens psychological distance between them and the learners and leads to greater learning. This is because there are verbal aspects like giving praise, soliciting for viewpoints, humor, etc and non-verbal expressions like eye contact, facial expressions, gestures, etc which make teachers to be closer to learners psychologically (Kelley & Gorham, 2009 ).

Learner outcomes

The outcomes under scrutiny in this study include performance, motivation, satisfaction and knowledge construction. Motivation is seen here as an outcome because, much as cognitive factors such as course grades are used in measuring learning outcomes, affective factors like intrinsic motivation may also be used to indicate outcomes of learning (Kuo, Walker, Belland, & Schroder, 2013 ). Research shows that high motivation among online learners leads to persistence in their courses (Menager-Beeley, 2004 ). Sankaran and Bui ( 2001 ) indicated that less motivated learners performed poorly in knowledge tests while those with high learning motivation demonstrate high performance in academics (Green, Nelson, Martin, & Marsh, 2006 ). Lim and Kim, ( 2003 ) indicated that learner interest as a motivation factor promotes learner involvement in learning and this could lead to learning effectiveness in blended learning.

Learner satisfaction was noted as a strong factor for effectiveness of blended and online courses (Wilging & Johnson, 2009) and dissatisfaction may result from learners’ incompetence in the use of the learning management system as an effective learning tool since, as Islam ( 2014 ) puts it, users may be dissatisfied with an information system due to ease of use. A lack of prompt feedback for learners from course instructors was found to cause dissatisfaction in an online graduate course. In addition, dissatisfaction resulted from technical difficulties as well as ambiguous course instruction Hara and Kling ( 2001 ). These factors, once addressed, can lead to learner satisfaction in e-learning and blended learning and eventual effectiveness. A study by Blocker and Tucker ( 2001 ) also showed that learners had difficulties with technology and inadequate group participation by peers leading to dissatisfaction within these design features. Student-teacher interactions are known to bring satisfaction within online courses. Study results by Swan ( 2001 ) indicated that student-teacher interaction strongly related with student satisfaction and high learner-learner interaction resulted in higher levels of course satisfaction. Descriptive results by Naaj, Nachouki, and Ankit ( 2012 ) showed that learners were satisfied with technology which was a video-conferencing component of blended learning with a mean of 3.7. The same study indicated student satisfaction with instructors at a mean of 3.8. Askar and Altun, ( 2008 ) found that learners were satisfied with face-to-face sessions of the blend with t-tests and ANOVA results indicating female scores as higher than for males in the satisfaction with face-to-face environment of the blended learning.

Studies comparing blended learning with traditional face-to-face have indicated that learners perform equally well in blended learning and their performance is unaffected by the delivery method (Kwak, Menezes, & Sherwood, 2013 ). In another study, learning experience and performance are known to improve when traditional course delivery is integrated with online learning (Stacey & Gerbic, 2007 ). Such improvement as noted may be an indicator of blended learning effectiveness. Our study however, delves into improved performance but seeks to establish the potential of blended learning effectiveness by considering grades obtained in a blended learning experiment. Score 50 and above is considered a pass in this study’s setting and learners scoring this and above will be considered to have passed. This will make our conclusions about the potential of blended learning effectiveness.

Regarding knowledge construction, it has been noted that effective learning occurs where learners are actively involved (Nurmela, Palonen, Lehtinen & Hakkarainen, 2003 , cited in Zhu, 2012 ) and this may be an indicator of learning environment effectiveness. Effective blended learning would require that learners are able to initiate, discover and accomplish the processes of knowledge construction as antecedents of blended learning effectiveness. A study by Rahman, Yasin and Jusoff ( 2011 ) indicated that learners were able to use some steps to construct meaning through an online discussion process through assignments given. In the process of giving and receiving among themselves, the authors noted that learners learned by writing what they understood. From our perspective, this can be considered to be accomplishment in the knowledge construction process. Their study further shows that learners construct meaning individually from assignments and this stage is referred to as pre-construction which for our study, is an aspect of discovery in the knowledge construction process.

Predictors of blended learning effectiveness

Researchers have dealt with success factors for online learning or those for traditional face-to-face learning but little is known about factors that predict blended learning effectiveness in view of learner characteristics and blended learning design features. This part of our study seeks to establish the learner characteristics/backgrounds and design features that predict blended learning effectiveness with regard to satisfaction, outcomes, motivation and knowledge construction. Song, Singleton, Hill, and Koh ( 2004 ) examined online learning effectiveness factors and found out that time management (a self-regulatory factor) was crucial for successful online learning. Eom, Wen, and Ashill ( 2006 ) using a survey found out that interaction, among other factors, was significant for learner satisfaction. Technical problems with regard to instructional design were a challenge to online learners thus not indicating effectiveness (Song et al., 2004 ), though the authors also indicated that descriptive statistics to a tune of 75% and time management (62%) impact on success of online learning. Arbaugh ( 2000 ) and Swan ( 2001 ) indicated that high levels of learner-instructor interaction are associated with high levels of user satisfaction and learning outcomes. A study by Naaj et al. ( 2012 ) indicated that technology and learner interactions, among other factors, influenced learner satisfaction in blended learning.

Objective and research questions of the current study

The objective of the current study is to investigate the effectiveness of blended learning in view of student satisfaction, knowledge construction, performance and intrinsic motivation and how they are related to student characteristics and blended learning design features in a blended learning environment.

Research questions

What are the student characteristics and blended learning design features for an effective blended learning environment?

Which factors (among the learner characteristics and blended learning design features) predict student satisfaction, learning outcomes, intrinsic motivation and knowledge construction?

Conceptual model of the present study

The reviewed literature clearly shows learner characteristics/background and blended learning design features play a part in blended learning effectiveness and some of them are significant predictors of effectiveness. The conceptual model for our study is depicted as follows (Fig.  1 ):

Conceptual model of the current study

Research design

This research applies a quantitative design where descriptive statistics are used for the student characteristics and design features data, t-tests for the age and gender variables to determine if they are significant in blended learning effectiveness and regression for predictors of blended learning effectiveness.

This study is based on an experiment in which learners participated during their study using face-to-face sessions and an on-line session of a blended learning design. A learning management system (Moodle) was used and learner characteristics/background and blended learning design features were measured in relation to learning effectiveness. It is therefore a planning evaluation research design as noted by Guskey ( 2000 ) since the outcomes are aimed at blended learning implementation at MMU. The plan under which the various variables were tested involved face-to-face study at the beginning of a 17 week semester which was followed by online teaching and learning in the second half of the semester. The last part of the semester was for another face-to-face to review work done during the online sessions and final semester examinations. A questionnaire with items on student characteristics, design features and learning outcomes was distributed among students from three schools and one directorate of postgraduate studies.

Participants

Cluster sampling was used to select a total of 238 learners to participate in this study. Out of the whole university population of students, three schools and one directorate were used. From these, one course unit was selected from each school and all the learners following the course unit were surveyed. In the school of Education ( n  = 70) and Business and Management Studies ( n  = 133), sophomore students were involved due to the fact that they have been introduced to ICT basics during their first year of study. Students of the third year were used from the department of technology in the School of Applied Sciences and Technology ( n  = 18) since most of the year two courses had a lot of practical aspects that could not be used for the online learning part. From the Postgraduate Directorate ( n  = 17), first and second year students were selected because learners attend a face-to-face session before they are given paper modules to study away from campus.

The study population comprised of 139 male students representing 58.4% and 99 females representing 41.6% with an average age of 24 years.

Instruments

The end of semester results were used to measure learner performance. The online self-regulated learning questionnaire (Barnard, Lan, To, Paton, & Lai, 2009 ) and the intrinsic motivation inventory (Deci & Ryan, 1982 ) were applied to measure the constructs on self regulation in the student characteristics and motivation in the learning outcome constructs. Other self-developed instruments were used for the other remaining variables of attitudes, computer competence, workload management, social and family support, satisfaction, knowledge construction, technology quality, interactions, learning management system tools and resources and face-to-face support.

Instrument reliability

Cronbach’s alpha was used to test reliability and the table below gives the results. All the scales and sub-scales had acceptable internal consistency reliabilities as shown in Table  1 below:

Data analysis

First, descriptive statistics was conducted. Shapiro-Wilk test was done to test normality of the data for it to qualify for parametric tests. The test results for normality of our data before the t- test resulted into significant levels (Male = .003, female = .000) thereby violating the normality assumption. We therefore used the skewness and curtosis results which were between −1.0 and +1.0 and assumed distribution to be sufficiently normal to qualify the data for a parametric test, (Pallant, 2010 ). An independent samples t -test was done to find out the differences in male and female performance to explain the gender characteristics in blended learning effectiveness. A one-way ANOVA between subjects was conducted to establish the differences in performance between age groups. Finally, multiple regression analysis was done between student variables and design elements with learning outcomes to determine the significant predictors for blended learning effectiveness.

Student characteristics, blended learning design features and learning outcomes ( RQ1 )

A t- test was carried out to establish the performance of male and female learners in the blended learning set up. This was aimed at finding out if male and female learners do perform equally well in blended learning given their different roles and responsibilities in society. It was found that male learners performed slightly better ( M  = 62.5) than their female counterparts ( M  = 61.1). An independent t -test revealed that the difference between the performances was not statistically significant ( t  = 1.569, df = 228, p  = 0.05, one tailed). The magnitude of the differences in the means is small with effect size ( d  = 0.18). A one way between subjects ANOVA was conducted on the performance of different age groups to establish the performance of learners of young and middle aged age groups (20–30, young & and 31–39, middle aged). This revealed a significant difference in performance (F(1,236 = 8.498, p < . 001).

Average percentages of the items making up the self regulated learning scale are used to report the findings about all the sub-scales in the learner characteristics/background scale. Results show that learner self-regulation was good enough at 72.3% in all the sub-scales of goal setting, environment structuring, task strategies, time management, help-seeking and self-evaluation among learners. The least in the scoring was task strategies at 67.7% and the highest was learner environment structuring at 76.3%. Learner attitude towards blended learning environment is at 76% in the sub-scales of learner autonomy, quality of instructional materials, course structure, course interface and interactions. The least scored here is attitude to course structure at 66% and their attitudes were high on learner autonomy and course interface both at 82%. Results on the learners’ computer competences are summarized in percentages in the table below (Table  2 ):

It can be seen that learners are skilled in word processing at 91%, email at 63.5%, spreadsheets at 68%, web browsers at 70.2% and html tools at 45.4%. They are therefore good enough in word processing and web browsing. Their computer confidence levels are reported at 75.3% and specifically feel very confident when it comes to working with a computer (85.7%). Levels of family and social support for learners during blended learning experiences are at 60.5 and 75% respectively. There is however a low score on learners being assisted by family members in situations of computer setbacks (33.2%) as 53.4% of the learners reported no assistance in this regard. A higher percentage (85.3%) is reported on learners getting support from family regarding provision of essentials for learning such as tuition. A big percentage of learners spend two hours on study while at home (35.3%) followed by one hour (28.2%) while only 9.7% spend more than three hours on study at home. Peers showed great care during the blended learning experience (81%) and their experiences were appreciated by the society (66%). Workload management by learners vis-à-vis studying is good at 60%. Learners reported that their workmates stand in for them at workplaces to enable them do their study in blended learning while 61% are encouraged by their bosses to go and improve their skills through further education and training. On the time spent on other activities not related to study, majority of the learners spend three hours (35%) while 19% spend 6 hours. Sixty percent of the learners have to answer to someone when they are not attending to other activities outside study compared to the 39.9% who do not and can therefore do study or those other activities.

The usability of the online system, tools and resources was below average as shown in the table below in percentages (Table  3 ):

However, learners became skilled at navigating around the learning management system (79%) and it was easy for them to locate course content, tools and resources needed such as course works, news, discussions and journal materials. They effectively used the communication tools (60%) and to work with peers by making posts (57%). They reported that online resources were well organized, user friendly and easy to access (71%) as well as well structured in a clear and understandable manner (72%). They therefore recommended the use of online resources for other course units in future (78%) because they were satisfied with them (64.3%). On the whole, the online resources were fine for the learners (67.2%) and useful as a learning resource (80%). The learners’ perceived usefulness/satisfaction with online system, tools, and resources was at 81% as the LMS tools helped them to communicate, work with peers and reflect on their learning (74%). They reported that using moodle helped them to learn new concepts, information and gaining skills (85.3%) as well as sharing what they knew or learned (76.4%). They enjoyed the course units (78%) and improved their skills with technology (89%).

Learner interactions were seen from three angles of cognitivism, collaborative learning and student-teacher interactions. Collaborative learning was average at 50% with low percentages in learners posting challenges to colleagues’ ideas online (34%) and posting ideas for colleagues to read online (37%). They however met oftentimes online (60%) and organized how they would work together in study during the face-to-face meetings (69%). The common form of communication medium frequently used by learners during the blended learning experience was by phone (34.5%) followed by whatsapp (21.8%), face book (21%), discussion board (11.8%) and email (10.9%). At the cognitive level, learners interacted with content at 72% by reading the posted content (81%), exchanging knowledge via the LMS (58.4%), participating in discussions on the forum (62%) and got course objectives and structure introduced during the face-to-face sessions (86%). Student-teacher interaction was reported at 71% through instructors individually working with them online (57.2%) and being well guided towards learning goals (81%). They did receive suggestions from instructors about resources to use in their learning (75.3%) and instructors provided learning input for them to come up with their own answers (71%).

The technology quality during the blended learning intervention was rated at 69% with availability of 72%, quality of the resources was at 68% with learners reporting that discussion boards gave right content necessary for study (71%) and the email exchanges containing relevant and much needed information (63.4%) as well as chats comprising of essential information to aid the learning (69%). Internet reliability was rated at 66% with a speed considered averagely good to facilitate online activities (63%). They however reported that there was intermittent breakdown during online study (67%) though they could complete their internet program during connection (63.4%). Learners eventually found it easy to download necessary materials for study in their blended learning experiences (71%).

Learner extent of use of the learning management system features was as shown in the table below in percentage (Table  4 ):

From the table, very rarely used features include the blog and wiki while very often used ones include the email, forum, chat and calendar.

The effectiveness of the LMS was rated at 79% by learners reporting that they found it useful (89%) and using it makes their learning activities much easier (75.2%). Moodle has helped learners to accomplish their learning tasks more quickly (74%) and that as a LMS, it is effective in teaching and learning (88%) with overall satisfaction levels at 68%. However, learners note challenges in the use of the LMS regarding its performance as having been problematic to them (57%) and only 8% of the learners reported navigation while 16% reported access as challenges.

Learner attitudes towards Face-to-face support were reported at 88% showing that the sessions were enjoyable experiences (89%) with high quality class discussions (86%) and therefore recommended that the sessions should continue in blended learning (89%). The frequency of the face-to-face sessions is shown in the table below as preferred by learners (Table  5 ).

Learners preferred face-to-face sessions after every month in the semester (33.6%) and at the beginning of the blended learning session only (27.7%).

Learners reported high intrinsic motivation levels with interest and enjoyment of tasks at 83.7%, perceived competence at 70.2%, effort/importance sub-scale at 80%, pressure/tension reported at 54%. The pressure percentage of 54% arises from learners feeling nervous (39.2%) and a lot of anxiety (53%) while 44% felt a lot of pressure during the blended learning experiences. Learners however reported the value/usefulness of blended learning at 91% with majority believing that studying online and face-to-face had value for them (93.3%) and were therefore willing to take part in blended learning (91.2%). They showed that it is beneficial for them (94%) and that it was an important way of studying (84.3%).

Learner satisfaction was reported at 81% especially with instructors (85%) high percentage reported on encouraging learner participation during the course of study 93%, course content (83%) with the highest being satisfaction with the good relationship between the objectives of the course units and the content (90%), technology (71%) with a high percentage on the fact that the platform was adequate for the online part of the learning (76%), interactions (75%) with participation in class at 79%, and face-to-face sessions (91%) with learner satisfaction high on face-to-face sessions being good enough for interaction and giving an overview of the courses when objectives were introduced at 92%.

Learners’ knowledge construction was reported at 78% with initiation and discovery scales scoring 84% with 88% specifically for discovering the learning points in the course units. The accomplishment scale in knowledge construction scored 71% and specifically the fact that learners were able to work together with group members to accomplish learning tasks throughout the study of the course units (79%). Learners developed reports from activities (67%), submitted solutions to discussion questions (68%) and did critique peer arguments (69%). Generally, learners performed well in blended learning in the final examination with an average pass of 62% and standard deviation of 7.5.

Significant predictors of blended learning effectiveness ( RQ 2)

A standard multiple regression analysis was done taking learner characteristics/background and design features as predictor variables and learning outcomes as criterion variables. The data was first tested to check if it met the linear regression test assumptions and results showed the correlations between the independent variables and each of the dependent variables (highest 0.62 and lowest 0.22) as not being too high, which indicated that multicollinearity was not a problem in our model. From the coefficients table, the VIF values ranged from 1.0 to 2.4, well below the cut off value of 10 and indicating no possibility of multicollinearity. The normal probability plot was seen to lie as a reasonably straight diagonal from bottom left to top right indicating normality of our data. Linearity was found suitable from the scatter plot of the standardized residuals and was rectangular in distribution. Outliers were no cause for concern in our data since we had only 1% of all cases falling outside 3.0 thus proving the data as a normally distributed sample. Our R -square values was at 0.525 meaning that the independent variables explained about 53% of the variance in overall satisfaction, motivation and knowledge construction of the learners. All the models explaining the three dependent variables of learner satisfaction, intrinsic motivation and knowledge construction were significant at the 0.000 probability level (Table  6 ).

From the table above, design features (technology quality and online tools and resources), and learner characteristics (attitudes to blended learning, self-regulation) were significant predictors of learner satisfaction in blended learning. This means that good technology with the features involved and the learner positive attitudes with capacity to do blended learning with self drive led to their satisfaction. The design features (technology quality, interactions) and learner characteristics (self regulation and social support), were found to be significant predictors of learner knowledge construction. This implies that learners’ capacity to go on their work by themselves supported by peers and high levels of interaction using the quality technology led them to construct their own ideas in blended learning. Design features (technology quality, online tools and resources as well as learner interactions) and learner characteristics (self regulation), significantly predicted the learners’ intrinsic motivation in blended learning suggesting that good technology, tools and high interaction levels with independence in learning led to learners being highly motivated. Finally, none of the independent variables considered under this study were predictors of learning outcomes (grade).

In this study we have investigated learning outcomes as dependent variables to establish if particular learner characteristics/backgrounds and design features are related to the outcomes for blended learning effectiveness and if they predict learning outcomes in blended learning. We took students from three schools out of five and one directorate of post-graduate studies at a Ugandan University. The study suggests that the characteristics and design features examined are good drivers towards an effective blended learning environment though a few of them predicted learning outcomes in blended learning.

Student characteristics/background, blended learning design features and learning outcomes

The learner characteristics, design features investigated are potentially important for an effective blended learning environment. Performance by gender shows a balance with no statistical differences between male and female. There are statistically significant differences ( p  < .005) in the performance between age groups with means of 62% for age group 20–30 and 67% for age group 31 –39. The indicators of self regulation exist as well as positive attitudes towards blended learning. Learners do well with word processing, e-mail, spreadsheets and web browsers but still lag below average in html tools. They show computer confidence at 75.3%; which gives prospects for an effective blended learning environment in regard to their computer competence and confidence. The levels of family and social support for learners stand at 61 and 75% respectively, indicating potential for blended learning to be effective. The learners’ balance between study and work is a drive factor towards blended learning effectiveness since their management of their workload vis a vis study time is at 60 and 61% of the learners are encouraged to go for study by their bosses. Learner satisfaction with the online system and its tools shows prospect for blended learning effectiveness but there are challenges in regard to locating course content and assignments, submitting their work and staying on a task during online study. Average collaborative, cognitive learning as well as learner-teacher interactions exist as important factors. Technology quality for effective blended learning is a potential for effectiveness though features like the blog and wiki are rarely used by learners. Face-to-face support is satisfactory and it should be conducted every month. There is high intrinsic motivation, satisfaction and knowledge construction as well as good performance in examinations ( M  = 62%, SD = 7.5); which indicates potentiality for blended learning effectiveness.

Significant predictors of blended learning effectiveness

Among the design features, technology quality, online tools and face-to-face support are predictors of learner satisfaction while learner characteristics of self regulation and attitudes to blended learning are predictors of satisfaction. Technology quality and interactions are the only design features predicting learner knowledge construction, while social support, among the learner backgrounds, is a predictor of knowledge construction. Self regulation as a learner characteristic is a predictor of knowledge construction. Self regulation is the only learner characteristic predicting intrinsic motivation in blended learning while technology quality, online tools and interactions are the design features predicting intrinsic motivation. However, all the independent variables are not significant predictors of learning performance in blended learning.

The high computer competences and confidence is an antecedent factor for blended learning effectiveness as noted by Hadad ( 2007 ) and this study finds learners confident and competent enough for the effectiveness of blended learning. A lack in computer skills causes failure in e-learning and blended learning as noted by Shraim and Khlaif ( 2010 ). From our study findings, this is no threat for blended learning our case as noted by our results. Contrary to Cohen et al. ( 2012 ) findings that learners’ family responsibilities and hours of employment can impede their process of learning, it is not the case here since they are drivers to the blended learning process. Time conflict, as compounded by family, employment status and management support (Packham et al., 2004 ) were noted as causes of learner failure and drop out of online courses. Our results show, on the contrary, that these factors are drivers for blended learning effectiveness because learners have a good balance between work and study and are supported by bosses to study. In agreement with Selim ( 2007 ), learner positive attitudes towards e-and blended learning environments are success factors. In line with Coldwell et al. ( 2008 ), no statistically significant differences exist between age groups. We however note that Coldwel, et al dealt with young, middle-aged and old above 45 years whereas we dealt with young and middle aged only.

Learner interactions at all levels are good enough and contrary to Astleitner, ( 2000 ) that their absence makes learners withdraw, they are a drive factor here. In line with Loukis (2007) the LMS quality, reliability and ease of use lead to learning efficiency as technology quality, online tools are predictors of learner satisfaction and intrinsic motivation. Face-to-face sessions should continue on a monthly basis as noted here and is in agreement with Marriot et al. ( 2004 ) who noted learner preference for it for facilitating social interaction and communication skills. High learner intrinsic motivation leads to persistence in online courses as noted by Menager-Beeley, ( 2004 ) and is high enough in our study. This implies a possibility of an effectiveness blended learning environment. The causes of learner dissatisfaction noted by Islam ( 2014 ) such as incompetence in the use of the LMS are contrary to our results in our study, while the one noted by Hara and Kling, ( 2001 ) as resulting from technical difficulties and ambiguous course instruction are no threat from our findings. Student-teacher interaction showed a relation with satisfaction according to Swan ( 2001 ) but is not a predictor in our study. Initiating knowledge construction by learners for blended learning effectiveness is exhibited in our findings and agrees with Rahman, Yasin and Jusof ( 2011 ). Our study has not agreed with Eom et al. ( 2006 ) who found learner interactions as predictors of learner satisfaction but agrees with Naaj et al. ( 2012 ) regarding technology as a predictor of learner satisfaction.

Conclusion and recommendations

An effective blended learning environment is necessary in undertaking innovative pedagogical approaches through the use of technology in teaching and learning. An examination of learner characteristics/background, design features and learning outcomes as factors for effectiveness can help to inform the design of effective learning environments that involve face-to-face sessions and online aspects. Most of the student characteristics and blended learning design features dealt with in this study are important factors for blended learning effectiveness. None of the independent variables were identified as significant predictors of student performance. These gaps are open for further investigation in order to understand if they can be significant predictors of blended learning effectiveness in a similar or different learning setting.

In planning to design and implement blended learning, we are mindful of the implications raised by this study which is a planning evaluation research for the design and eventual implementation of blended learning. Universities should be mindful of the interplay between the learner characteristics, design features and learning outcomes which are indicators of blended learning effectiveness. From this research, learners manifest high potential to take on blended learning more especially in regard to learner self-regulation exhibited. Blended learning is meant to increase learners’ levels of knowledge construction in order to create analytical skills in them. Learner ability to assess and critically evaluate knowledge sources is hereby established in our findings. This can go a long way in producing skilled learners who can be innovative graduates enough to satisfy employment demands through creativity and innovativeness. Technology being less of a shock to students gives potential for blended learning design. Universities and other institutions of learning should continue to emphasize blended learning approaches through installation of learning management systems along with strong internet to enable effective learning through technology especially in the developing world.

Abubakar, D. & Adetimirin. (2015). Influence of computer literacy on post-graduates’ use of e-resources in Nigerian University Libraries. Library Philosophy and Practice. From http://digitalcommons.unl.edu/libphilprac/ . Retrieved 18 Aug 2015.

Ahmad, N., & Al-Khanjari, Z. (2011). Effect of Moodle on learning: An Oman perception. International Journal of Digital Information and Wireless Communications (IJDIWC), 1 (4), 746–752.

Google Scholar  

Anderson, T. (2004). Theory and Practice of Online Learning . Canada: AU Press, Athabasca University.

Arbaugh, J. B. (2000). How classroom environment and student engagement affect learning in internet-basedMBAcourses. Business Communication Quarterly, 63 (4), 9–18.

Article   Google Scholar  

Askar, P. & Altun, A. (2008). Learner satisfaction on blended learning. E-Leader Krakow , 2008.

Astleitner, H. (2000) Dropout and distance education. A review of motivational and emotional strategies to reduce dropout in web-based distance education. In Neuwe Medien in Unterricht, Aus-und Weiterbildung Waxmann Munster, New York.

Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S. (2009). Measuring self regulation in online and blended learning environments’. Internet and Higher Education, 12 (1), 1–6.

Beard, L. A., Harper, C., & Riley, G. (2004). Online versus on-campus instruction: student attitudes & perceptions. TechTrends, 48 (6), 29–31.

Berenson, R., Boyles, G., & Weaver, A. (2008). Emotional intelligence as a predictor for success in online learning. International Review of Research in open & Distance Learning, 9 (2), 1–16.

Blocker, J. M., & Tucker, G. (2001). Using constructivist principles in designing and integrating online collaborative interactions. In F. Fuller & R. McBride (Eds.), Distance education. Proceedings of the Society for Information Technology & Teacher Education International Conference (pp. 32–36). ERIC Document Reproduction Service No. ED 457 822.

Cohen, K. E., Stage, F. K., Hammack, F. M., & Marcus, A. (2012). Persistence of master’s students in the United States: Developing and testing of a conceptual model . USA: PhD Dissertation, New York University.

Coldwell, J., Craig, A., Paterson, T., & Mustard, J. (2008). Online students: Relationships between participation, demographics and academic performance. The Electronic Journal of e-learning, 6 (1), 19–30.

Deci, E. L., & Ryan, R. M. (1982). Intrinsic Motivation Inventory. Available from selfdeterminationtheory.org/intrinsic-motivation-inventory/ . Accessed 2 Aug 2016.

Delone, W. H., & McLean, E. R. (2003). The Delone and McLean model of information systems success: A Ten-year update. Journal of Management Information Systems, 19 (4), 9–30.

Demirkol, M., & Kazu, I. Y. (2014). Effect of blended environment model on high school students’ academic achievement. The Turkish Online Journal of Educational Technology, 13 (1), 78–87.

Eom, S., Wen, H., & Ashill, N. (2006). The determinants of students’ perceived learning outcomes and satisfaction in university online education: an empirical investigation’. Decision Sciences Journal of Innovative Education, 4 (2), 215–235.

Garrison, D. R., & Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. Internet and Higher Education, 7 (2), 95–105.

Goyal, E., & Tambe, S. (2015). Effectiveness of Moodle-enabled blended learning in private Indian Business School teaching NICHE programs. The Online Journal of New Horizons in Education, 5 (2), 14–22.

Green, J., Nelson, G., Martin, A. J., & Marsh, H. (2006). The causal ordering of self-concept and academic motivation and its effect on academic achievement. International Education Journal, 7 (4), 534–546.

Guskey, T. R. (2000). Evaluating Professional Development . Thousands Oaks: Corwin Press.

Hadad, W. (2007). ICT-in-education toolkit reference handbook . InfoDev. from http://www.infodev.org/en/Publication.301.html . Retrieved 04 Aug 2015.

Hara, N. & Kling, R. (2001). Student distress in web-based distance education. Educause Quarterly. 3 (2001).

Heinich, R., Molenda, M., Russell, J. D., & Smaldino, S. E. (2001). Instructional Media and Technologies for Learning (7th ed.). Englewood Cliffs: Prentice-Hall.

Hofmann, J. (2014). Solutions to the top 10 challenges of blended learning. Top 10 challenges of blended learning. Available on cedma-europe.org .

Islam, A. K. M. N. (2014). Sources of satisfaction and dissatisfaction with a learning management system in post-adoption stage: A critical incident technique approach. Computers in Human Behaviour, 30 , 249–261.

Kelley, D. H. & Gorham, J. (2009) Effects of immediacy on recall of information. Communication Education, 37 (3), 198–207.

Kenney, J., & Newcombe, E. (2011). Adopting a blended learning approach: Challenges, encountered and lessons learned in an action research study. Journal of Asynchronous Learning Networks, 15 (1), 45–57.

Kintu, M. J., & Zhu, C. (2016). Student characteristics and learning outcomes in a blended learning environment intervention in a Ugandan University. Electronic Journal of e-Learning, 14 (3), 181–195.

Kuo, Y., Walker, A. E., Belland, B. R., & Schroder, L. E. E. (2013). A predictive study of student satisfaction in online education programs. International Review of Research in Open and Distributed Learning, 14 (1), 16–39.

Kwak, D. W., Menezes, F. M., & Sherwood, C. (2013). Assessing the impact of blended learning on student performance. Educational Technology & Society, 15 (1), 127–136.

Lim, D. H., & Kim, H. J. (2003). Motivation and learner characteristics affecting online learning and learning application. Journal of Educational Technology Systems, 31 (4), 423–439.

Lim, D. H., & Morris, M. L. (2009). Learner and instructional factors influencing learner outcomes within a blended learning environment. Educational Technology & Society, 12 (4), 282–293.

Lin, B., & Vassar, J. A. (2009). Determinants for success in online learning communities. International Journal of Web-based Communities, 5 (3), 340–350.

Loukis, E., Georgiou, S. & Pazalo, K. (2007). A value flow model for the evaluation of an e-learning service. ECIS, 2007 Proceedings, paper 175.

Lynch, R., & Dembo, M. (2004). The relationship between self regulation and online learning in a blended learning context. The International Review of Research in Open and Distributed Learning, 5 (2), 1–16.

Marriot, N., Marriot, P., & Selwyn. (2004). Accounting undergraduates’ changing use of ICT and their views on using the internet in higher education-A Research note. Accounting Education, 13 (4), 117–130.

Menager-Beeley, R. (2004). Web-based distance learning in a community college: The influence of task values on task choice, retention and commitment. (Doctoral dissertation, University of Southern California). Dissertation Abstracts International, 64 (9-A), 3191.

Naaj, M. A., Nachouki, M., & Ankit, A. (2012). Evaluating student satisfaction with blended learning in a gender-segregated environment. Journal of Information Technology Education: Research, 11 , 185–200.

Nurmela, K., Palonen, T., Lehtinen, E. & Hakkarainen, K. (2003). Developing tools for analysing CSCL process. In Wasson, B. Ludvigsen, S. & Hoppe, V. (eds), Designing for change in networked learning environments (pp 333–342). Dordrecht, The Netherlands, Kluwer.

Osgerby, J. (2013). Students’ perceptions of the introduction of a blended learning environment: An exploratory case study. Accounting Education, 22 (1), 85–99.

Oxford Group, (2013). Blended learning-current use, challenges and best practices. From http://www.kineo.com/m/0/blended-learning-report-202013.pdf . Accessed on 17 Mar 2016.

Packham, G., Jones, P., Miller, C., & Thomas, B. (2004). E-learning and retention key factors influencing student withdrawal. Education and Training, 46 (6–7), 335–342.

Pallant, J. (2010). SPSS Survival Mannual (4th ed.). Maidenhead: OUP McGraw-Hill.

Park, J.-H., & Choi, H. J. (2009). Factors influencing adult learners’ decision to drop out or persist in online learning. Educational Technology & Society, 12 (4), 207–217.

Picciano, A., & Seaman, J. (2007). K-12 online learning: A survey of U.S. school district administrators . New York, USA: Sloan-C.

Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: a research framework and a preliminary assessment of effectiveness in basic IT skill training. MIS Quarterly, 25 (4), 401–426.

Pituch, K. A., & Lee, Y. K. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47 (2), 222–244.

Rahman, S. et al, (2011). Knowledge construction process in online learning. Middle East Journal of Scientific Research, 8 (2), 488–492.

Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. Computers & Education, 6 (1), 1–16.

Sankaran, S., & Bui, T. (2001). Impact of learning strategies and motivation on performance: A study in Web-based instruction. Journal of Instructional Psychology, 28 (3), 191–198.

Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49 (2), 396–413.

Shraim, K., & Khlaif, Z. N. (2010). An e-learning approach to secondary education in Palestine: opportunities and challenges. Information Technology for Development, 16 (3), 159–173.

Shrain, K. (2012). Moving towards e-learning paradigm: Readiness of higher education instructors in Palestine. International Journal on E-Learning, 11 (4), 441–463.

Song, L., Singleton, E. S., Hill, J. R., & Koh, M. H. (2004). Improving online learning: student perceptions of useful and challenging characteristics’. Internet and Higher Education, 7 (1), 59–70.

Stacey, E., & Gerbic, P. (2007). Teaching for blended learning: research perspectives from on-campus and distance students. Education and Information Technologies, 12 , 165–174.

Swan, K. (2001). Virtual interactivity: design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education, 22 (2), 306–331.

Article   MathSciNet   Google Scholar  

Thompson, E. (2004). Distance education drop-out: What can we do? In R. Pospisil & L. Willcoxson (Eds.), Learning Through Teaching (Proceedings of the 6th Annual Teaching Learning Forum, pp. 324–332). Perth, Australia: Murdoch University.

Tselios, N., Daskalakis, S., & Papadopoulou, M. (2011). Assessing the acceptance of a blended learning university course. Educational Technology & Society, 14 (2), 224–235.

Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to drop-out of online courses. Journal of Asynchronous Learning Networks, 13 (3), 115–127.

Zhu, C. (2012). Student satisfaction, performance and knowledge construction in online collaborative learning. Educational Technology & Society, 15 (1), 127–137.

Zielinski, D. (2000). Can you keep learners online? Training, 37 (3), 64–75.

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Kintu, M.J., Zhu, C. & Kagambe, E. Blended learning effectiveness: the relationship between student characteristics, design features and outcomes. Int J Educ Technol High Educ 14 , 7 (2017). https://doi.org/10.1186/s41239-017-0043-4

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Partisan divides over K-12 education in 8 charts

K-12 education is shaping up to be a key issue in the 2024 election cycle. Several prominent Republican leaders, including GOP presidential candidates, have sought to limit discussion of gender identity and race in schools , while the Biden administration has called for expanded protections for transgender students . The coronavirus pandemic also brought out partisan divides on many issues related to K-12 schools .

Today, the public is sharply divided along partisan lines on topics ranging from what should be taught in schools to how much influence parents should have over the curriculum. Here are eight charts that highlight partisan differences over K-12 education, based on recent surveys by Pew Research Center and external data.

Pew Research Center conducted this analysis to provide a snapshot of partisan divides in K-12 education in the run-up to the 2024 election. The analysis is based on data from various Center surveys and analyses conducted from 2021 to 2023, as well as survey data from Education Next, a research journal about education policy. Links to the methodology and questions for each survey or analysis can be found in the text of this analysis.

Most Democrats say K-12 schools are having a positive effect on the country , but a majority of Republicans say schools are having a negative effect, according to a Pew Research Center survey from October 2022. About seven-in-ten Democrats and Democratic-leaning independents (72%) said K-12 public schools were having a positive effect on the way things were going in the United States. About six-in-ten Republicans and GOP leaners (61%) said K-12 schools were having a negative effect.

About six-in-ten Democrats (62%) have a favorable opinion of the U.S. Department of Education , while a similar share of Republicans (65%) see it negatively, according to a March 2023 survey by the Center. Democrats and Republicans were more divided over the Department of Education than most of the other 15 federal departments and agencies the Center asked about.

In May 2023, after the survey was conducted, Republican lawmakers scrutinized the Department of Education’s priorities during a House Committee on Education and the Workforce hearing. The lawmakers pressed U.S. Secretary of Education Miguel Cardona on topics including transgender students’ participation in sports and how race-related concepts are taught in schools, while Democratic lawmakers focused on school shootings.

Partisan opinions of K-12 principals have become more divided. In a December 2021 Center survey, about three-quarters of Democrats (76%) expressed a great deal or fair amount of confidence in K-12 principals to act in the best interests of the public. A much smaller share of Republicans (52%) said the same. And nearly half of Republicans (47%) had not too much or no confidence at all in principals, compared with about a quarter of Democrats (24%).

This divide grew between April 2020 and December 2021. While confidence in K-12 principals declined significantly among people in both parties during that span, it fell by 27 percentage points among Republicans, compared with an 11-point decline among Democrats.

Democrats are much more likely than Republicans to say teachers’ unions are having a positive effect on schools. In a May 2022 survey by Education Next , 60% of Democrats said this, compared with 22% of Republicans. Meanwhile, 53% of Republicans and 17% of Democrats said that teachers’ unions were having a negative effect on schools. (In this survey, too, Democrats and Republicans include independents who lean toward each party.)

The 38-point difference between Democrats and Republicans on this question was the widest since Education Next first asked it in 2013. However, the gap has exceeded 30 points in four of the last five years for which data is available.

Republican and Democratic parents differ over how much influence they think governments, school boards and others should have on what K-12 schools teach. About half of Republican parents of K-12 students (52%) said in a fall 2022 Center survey that the federal government has too much influence on what their local public schools are teaching, compared with two-in-ten Democratic parents. Republican K-12 parents were also significantly more likely than their Democratic counterparts to say their state government (41% vs. 28%) and their local school board (30% vs. 17%) have too much influence.

On the other hand, more than four-in-ten Republican parents (44%) said parents themselves don’t have enough influence on what their local K-12 schools teach, compared with roughly a quarter of Democratic parents (23%). A larger share of Democratic parents – about a third (35%) – said teachers don’t have enough influence on what their local schools teach, compared with a quarter of Republican parents who held this view.

Republican and Democratic parents don’t agree on what their children should learn in school about certain topics. Take slavery, for example: While about nine-in-ten parents of K-12 students overall agreed in the fall 2022 survey that their children should learn about it in school, they differed by party over the specifics. About two-thirds of Republican K-12 parents said they would prefer that their children learn that slavery is part of American history but does not affect the position of Black people in American society today. On the other hand, 70% of Democratic parents said they would prefer for their children to learn that the legacy of slavery still affects the position of Black people in American society today.

Parents are also divided along partisan lines on the topics of gender identity, sex education and America’s position relative to other countries. Notably, 46% of Republican K-12 parents said their children should not learn about gender identity at all in school, compared with 28% of Democratic parents. Those shares were much larger than the shares of Republican and Democratic parents who said that their children should not learn about the other two topics in school.

Many Republican parents see a place for religion in public schools , whereas a majority of Democratic parents do not. About six-in-ten Republican parents of K-12 students (59%) said in the same survey that public school teachers should be allowed to lead students in Christian prayers, including 29% who said this should be the case even if prayers from other religions are not offered. In contrast, 63% of Democratic parents said that public school teachers should not be allowed to lead students in any type of prayers.

In June 2022, before the Center conducted the survey, the Supreme Court ruled in favor of a football coach at a public high school who had prayed with players at midfield after games. More recently, Texas lawmakers introduced several bills in the 2023 legislative session that would expand the role of religion in K-12 public schools in the state. Those proposals included a bill that would require the Ten Commandments to be displayed in every classroom, a bill that would allow schools to replace guidance counselors with chaplains, and a bill that would allow districts to mandate time during the school day for staff and students to pray and study religious materials.

Mentions of diversity, social-emotional learning and related topics in school mission statements are more common in Democratic areas than in Republican areas. K-12 mission statements from public schools in areas where the majority of residents voted Democratic in the 2020 general election are at least twice as likely as those in Republican-voting areas to include the words “diversity,” “equity” or “inclusion,” according to an April 2023 Pew Research Center analysis .

Also, about a third of mission statements in Democratic-voting areas (34%) use the word “social,” compared with a quarter of those in Republican-voting areas, and a similar gap exists for the word “emotional.” Like diversity, equity and inclusion, social-emotional learning is a contentious issue between Democrats and Republicans, even though most K-12 parents think it’s important for their children’s schools to teach these skills . Supporters argue that social-emotional learning helps address mental health needs and student well-being, but some critics consider it emotional manipulation and want it banned.

In contrast, there are broad similarities in school mission statements outside of these hot-button topics. Similar shares of mission statements in Democratic and Republican areas mention students’ future readiness, parent and community involvement, and providing a safe and healthy educational environment for students.

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About 1 in 4 U.S. teachers say their school went into a gun-related lockdown in the last school year

About half of americans say public k-12 education is going in the wrong direction, what public k-12 teachers want americans to know about teaching, what’s it like to be a teacher in america today, race and lgbtq issues in k-12 schools, most popular.

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• April 2024: UB researcher receives grant to study oral histories of Black world language teachers

Published April 18, 2024

BY SARA DEMBSKI

Ub researcher receives grant to study oral histories of black world language teachers.

Tasha Austin , assistant professor of learning and instruction in the University at Buffalo Graduate School of Education, was awarded a prestigious Spencer Foundation Small Research Grant in the amount of $47,124. Beginning in February 2024, the two-year project will allow Austin to continue researching the intersection of Blackness and bi/multilingualism for professionals who have become world language (WL) teachers.

Her project, “Excavating the Oral Histories of Black World Language Teachers,” will conduct oral history interviews to help fill the gap in research through discrepant case sampling to learn what compels Black teachers to persist towards becoming WL professionals.

“Tasha Austin is rapidly earning a reputation for her insightful and compelling scholarship. This Spencer Foundation grant is a reflection of her strength as a researcher and the novel ways she chooses to conduct her research. I am so excited to see the outcomes of this project,” said GSE Dean and Professor Suzanne Rosenblith .

After joining GSE’s faculty in 2022, Austin had the opportunity to discuss her research interests with Rosenblith, prompting her to explore grant opportunities.

“We were talking about some of the courses that folks are taking to become teachers, and how when they get to the point of trying to figure out how to overcome some of these systemic inequities, it can be demoralizing, because once you realize that they exist, it's almost like they're everywhere,” Austin said. “And so, I was sharing with Dean Rosenblith that what frustrates me is that it's not that they've not been able to overcome before, and it's not that Black folks aren't always navigating these systems and finding ways to do it successfully.

“I just felt like all of the stories about that success are kind of reduced to these superhero kind of stories—like it has to be particular people, like MLK. When we talked about the commonplace efforts of Black educators, I began to bring up world language teachers and how, for all intents and purposes, it's really a negligible amount of Black world language teachers,” Austin continued. “Last time I checked, 2.5% of teachers are Black world language teachers. And so, together, we were thinking about the power of having those stories really nuanced and talked about.”

The main goal of Austin’s research is to learn how this group of Black WL teachers can be supported and increased. This is especially important now since, according to Austin’s research, there has been a 44% drop in conferred WL degrees over the last decade.

With this absence of Black WL teachers, students lose African American traditions and principles in the classroom. Austin reports that the cultural mismatch between educators and students, largely along racial lines, negatively affects students’ performance in school. Although racial and cultural overlap doesn’t automatically mean a good academic standing, Black educators do bring a tradition of teaching excellence and their knowledge of navigating anti-Blackness.

Tasha Austin, assistant professor of learning and instruction

A secondary goal for Austin is bringing to light that this type of research is not simply done by one person. “The entirety of the process is rooted in this desire to draw together these kinds of everyday Black folks. Now, these are scholars, but I still say they’re ‘everyday’ because having a degree doesn't make you a scholar, right? But I could not have done it without them,” she said. “And my plan is to continue to draw together these folks who have these capacities and these insights. I definitely don't see it as something that I can do alone.”

Austin expresses gratitude for those who have helped uplift her as she has pursued her research endeavors, including Betina Hsieh, associate professor at California State University, Long Beach’s College of Education; Dawnavyn James, GSE PhD student; Aminah Raysor, GSE PhD student; Uju Anya, associate professor at Carnegie Mellon University; Aris Clemons, assistant professor at the University of Tennessee, Knoxville; Anne Charity Hudley, associate dean of educational affairs and professor at Stanford University; Jamie Thomas, dean of social sciences at Cypress University; LJ Randolph, assistant professor at the University of Wisconsin-Madison; Ryuko Kubota, professor at the University of British Columbia; Theresa Austin, professor at University of Massachusetts Amherst; Geneva Smitherman, professor at Michigan State University; April Baker Bell, associate professor at Syracuse University; Marcelle Haddix, dean and professor at Syracuse University; Cheryl McLean, associate professor at Rutgers University; Michéle Foster, professor of urban education at the University of Louisville; and Nelson Flores, associate professor at the University of Pennsylvania.

“Without these folks, I wouldn't be able to make such an intervention because I draw on their work to substantiate the value that my work might bring,” Austin said. “And I'm missing 1000 names, right? But it feels important to not ever get any kind of recognition or elevation of what I'm doing without bringing in the folks in the room that make it possible.”