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Research Methods and Methodologies in Education

• Robert Coe - Evidence Based Education, UK
• Michael Waring - University of Leeds, UK 
• Larry V Hedges - Northwestern University, USA
• Laura Day Ashley - University of Birmingham, UK
• Description

The #1 resource for carrying out educational research as part of postgraduate study.

High-quality educational research requires careful consideration of every aspect of the process. This all-encompassing textbook written by leading international experts gives students and early career researchers a considered overview of principles that underpin research, and key qualitative, quantitative and mixed methods for research design, data collection and analysis.

This third edition includes  four  new chapters:

• Disseminating your research
• Data science and computational research methods
• Observational methods
• Analysis of variance (ANOVA)

Plus a new  Research essentials  feature that highlights key ‘must-haves’ or misconceptions relating to each methodological approach, research design or analytical tool discussed.

This is essential reading for postgraduate students on education courses and early career researchers looking to sharpen their research practice.

Logically structured, clear and informative. This book has significant chapter on Academic ethics which will be essential not only for BA students but for PhD and early research career as well

This book covers a wide range of issues in relation to educational research - there is something in there for all my students. Each chapter is short and to the point.

Research Methods and Methodologies in Education is a book I have used repeatedly since teaching Research on Foundation degree and BA top up

This book is beneficial for doctoral students because it provides clear and concise details on the steps to performing scholarly research designs. I am highly recommending this book for my courses.

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Designing Research in Education: Concepts and Methodologies

• Edited by: Jon Swain
• Publisher: SAGE Publications Ltd
• Publication year: 2017
• Online pub date: January 19, 2023
• Discipline: Education
• Methods: Case study research , Mixed methods , Research questions
• DOI: https:// doi. org/10.4135/9781529622775
• Keywords: knowledge , population , students , supervisors , surveying , teaching , theses Show all Show less
• Print ISBN: 9781446294260
• Online ISBN: 9781529622775
• Buy the book icon link

Subject index

This is a clear introduction to the methodological and philosophical debates in the field of education research. It sets out the key ideas, questions, and dilemmas which inform all research and then, through the careful use of case studies and practical advice from experienced researchers, grounds them in the specific concerns of education and educational studies. Written by experienced academics and teachers the book links broad philosophical principles with practical strategies for designing and conducting ethical and effective research. Perfect for postgraduate students planning their own research in education this book will help you to: • Understand the philosophical foundations of your work. • Conceptualise and refine your research question. • Pick the right methodology for your research. • Embed ethical considerations throughout your research. This book is an ideal companion for any postgraduate student or early career academic conducting research across education and educational studies.

Front Matter

• The Companion Website
• List of Abbreviations
• About the Authors
• Introduction

Part I: Concepts and philosophical issues informing research designs

• Chapter 1: Setting the scene in educational research
• Chapter 2: Designing and managing your research in education in the early stages
• Chapter 3: Designing your research in education
• Chapter 4: Constructing knowledge through social research: Debates in epistemology and ontology
• Chapter 5: Ethical issues and considerations

Part II: The application of the research designs

• Chapter 6: Experimental design
• Chapter 7: Surveys
• Chapter 8: Ethnography
• Chapter 9: Case studies
• Chapter 10: Mixed methods in education research
• Chapter 11: Summary and conclusions

Back Matter

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Conducting Quantitative Research in Education

• © 2020
• Saiyidi Mat Roni 0 ,
• Margaret Kristin Merga 1 ,
• Julia Elizabeth Morris 2

School of Business and Law, Edith Cowan University, Joondalup, Australia

You can also search for this author in PubMed   Google Scholar

School of Education, Edith Cowan University, Perth, Australia

School of education, edith cowan university, mount lawley, australia.

• Presents a practical guide on conducting quantitative research in the field of education
• Stresses the practical of use of non-parametric tests in quantitative research
• Provides educational researchers with the tools they can work with to achieve results efficiently

42k Accesses

45 Citations

6 Altmetric

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• Multivariate analysis
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Table of contents (10 chapters)

Front matter, introduction.

• Saiyidi Mat Roni, Margaret Kristin Merga, Julia Elizabeth Morris

Getting Started: What, Where, Why

Conducting research with children and students, data types and samples, data preparation, analysis: difference between groups, analysis: correlation, analysis: regression, write up and research translation, conclusion and further reading, back matter, authors and affiliations.

Saiyidi Mat Roni

Margaret Kristin Merga

Julia Elizabeth Morris

About the authors

Bibliographic information.

Book Title : Conducting Quantitative Research in Education

Authors : Saiyidi Mat Roni, Margaret Kristin Merga, Julia Elizabeth Morris

DOI : https://doi.org/10.1007/978-981-13-9132-3

Publisher : Springer Singapore

eBook Packages : Business and Management , Business and Management (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

Hardcover ISBN : 978-981-13-9131-6 Published: 24 August 2019

Softcover ISBN : 978-981-13-9134-7 Published: 25 August 2020

eBook ISBN : 978-981-13-9132-3 Published: 12 August 2019

Edition Number : 1

Number of Pages : VIII, 201

Number of Illustrations : 15 b/w illustrations, 127 illustrations in colour

Topics : Management Education , Big Data/Analytics , Statistics for Social Sciences, Humanities, Law

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Artificial Intelligence and Education: A Reading List

A bibliography to help educators prepare students and themselves for a future shaped by AI—with all its opportunities and drawbacks.

How should education change to address, incorporate, or challenge today’s AI systems, especially powerful large language models? What role should educators and scholars play in shaping the future of generative AI? The release of ChatGPT in November 2022 triggered an explosion of news, opinion pieces, and social media posts addressing these questions. Yet many are not aware of the current and historical body of academic work that offers clarity, substance, and nuance to enrich the discourse.

Linking the terms “AI” and “education” invites a constellation of discussions. This selection of articles is hardly comprehensive, but it includes explanations of AI concepts and provides historical context for today’s systems. It describes a range of possible educational applications as well as adverse impacts, such as learning loss and increased inequity. Some articles touch on philosophical questions about AI in relation to learning, thinking, and human communication. Others will help educators prepare students for civic participation around concerns including information integrity, impacts on jobs, and energy consumption. Yet others outline educator and student rights in relation to AI and exhort educators to share their expertise in societal and industry discussions on the future of AI.

Nabeel Gillani, Rebecca Eynon, Catherine Chiabaut, and Kelsey Finkel, “ Unpacking the ‘Black Box’ of AI in Education ,” Educational Technology & Society 26, no. 1 (2023): 99–111.

Whether we’re aware of it or not, AI was already widespread in education before ChatGPT. Nabeel Gillani et al. describe AI applications such as learning analytics and adaptive learning systems, automated communications with students, early warning systems, and automated writing assessment. They seek to help educators develop literacy around the capacities and risks of these systems by providing an accessible introduction to machine learning and deep learning as well as rule-based AI. They present a cautious view, calling for scrutiny of bias in such systems and inequitable distribution of risks and benefits. They hope that engineers will collaborate deeply with educators on the development of such systems.

Jürgen Rudolph, Samson Tan, and Shannon Tan, “ ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher Education? ” The Journal of Applied Learning and Teaching 6, no. 1 (January 24, 2023).

Jürgen Rudolph et al. give a practically oriented overview of ChatGPT’s implications for higher education. They explain the statistical nature of large language models as they tell the history of OpenAI and its attempts to mitigate bias and risk in the development of ChatGPT. They illustrate ways ChatGPT can be used with examples and screenshots. Their literature review shows the state of artificial intelligence in education (AIEd) as of January 2023. An extensive list of challenges and opportunities culminates in a set of recommendations that emphasizes explicit policy as well as expanding digital literacy education to include AI.

Emily M. Bender, Timnit Gebru, Angela McMillan-Major, and Shmargaret Shmitchell, “ On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 ,” FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (March 2021): 610–623.

Student and faculty understanding of the risks and impacts of large language models is central to AI literacy and civic participation around AI policy. This hugely influential paper details documented and likely adverse impacts of the current data-and-resource-intensive, non-transparent mode of development of these models. Bender et al. emphasize the ways in which these costs will likely be borne disproportionately by marginalized groups. They call for transparency around the energy use and cost of these models as well as transparency around the data used to train them. They warn that models perpetuate and even amplify human biases and that the seeming coherence of these systems’ outputs can be used for malicious purposes even though it doesn’t reflect real understanding.

The authors argue that inclusive participation in development can encourage alternate development paths that are less resource intensive. They further argue that beneficial applications for marginalized groups, such as improved automatic speech recognition systems, must be accompanied by plans to mitigate harm.

Erik Brynjolfsson, “ The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence ,” Daedalus 151, no. 2 (2022): 272–87.

Erik Brynjolfsson argues that when we think of artificial intelligence as aiming to substitute for human intelligence, we miss the opportunity to focus on how it can complement and extend human capabilities. Brynjolfsson calls for policy that shifts AI development incentives away from automation toward augmentation. Automation is more likely to result in the elimination of lower-level jobs and in growing inequality. He points educators toward augmentation as a framework for thinking about AI applications that assist learning and teaching. How can we create incentives for AI to support and extend what teachers do rather than substituting for teachers? And how can we encourage students to use AI to extend their thinking and learning rather than using AI to skip learning?

Kevin Scott, “ I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale ,” Daedalus 151, no. 2 (2022): 75–84.

Brynjolfsson’s focus on AI as “augmentation” converges with Microsoft computer scientist Kevin Scott’s focus on “cognitive assistance.” Steering discussion of AI away from visions of autonomous systems with their own goals, Scott argues that near-term AI will serve to help humans with cognitive work. Scott situates this assistance in relation to evolving historical definitions of work and the way in which tools for work embody generalized knowledge about specific domains. He’s intrigued by the way deep neural networks can represent domain knowledge in new ways, as seen in the unexpected coding capabilities offered by OpenAI’s GPT-3 language model, which have enabled people with less technical knowledge to code. His article can help educators frame discussions of how students should build knowledge and what knowledge is still relevant in contexts where AI assistance is nearly ubiquitous.

Laura D. Tyson and John Zysman, “ Automation, AI & Work ,” Daedalus 151, no. 2 (2022): 256–71.

How can educators prepare students for future work environments integrated with AI and advise students on how majors and career paths may be affected by AI automation? And how can educators prepare students to participate in discussions of government policy around AI and work? Laura Tyson and John Zysman emphasize the importance of policy in determining how economic gains due to AI are distributed and how well workers weather disruptions due to AI. They observe that recent trends in automation and gig work have exacerbated inequality and reduced the supply of “good” jobs for low- and middle-income workers. They predict that AI will intensify these effects, but they point to the way collective bargaining, social insurance, and protections for gig workers have mitigated such impacts in countries like Germany. They argue that such interventions can serve as models to help frame discussions of intelligent labor policies for “an inclusive AI era.”

Todd C. Helmus, Artificial Intelligence, Deepfakes, and Disinformation: A Primer (RAND Corporation, 2022).

Educators’ considerations of academic integrity and AI text can draw on parallel discussions of authenticity and labeling of AI content in other societal contexts. Artificial intelligence has made deepfake audio, video, and images as well as generated text much more difficult to detect as such. Here, Todd Helmus considers the consequences to political systems and individuals as he offers a review of the ways in which these can and have been used to promote disinformation. He considers ways to identify deepfakes and ways to authenticate provenance of videos and images. Helmus advocates for regulatory action, tools for journalistic scrutiny, and widespread efforts to promote media literacy. As well as informing discussions of authenticity in educational contexts, this report might help us shape curricula to teach students about the risks of deepfakes and unlabeled AI.

William Hasselberger, “ Can Machines Have Common Sense? ” The New Atlantis 65 (2021): 94–109.

Students, by definition, are engaged in developing their cognitive capacities; their understanding of their own intelligence is in flux and may be influenced by their interactions with AI systems and by AI hype. In his review of The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do by Erik J. Larson, William Hasselberger warns that in overestimating AI’s ability to mimic human intelligence we devalue the human and overlook human capacities that are integral to everyday life decision making, understanding, and reasoning. Hasselberger provides examples of both academic and everyday common-sense reasoning that continue to be out of reach for AI. He provides a historical overview of debates around the limits of artificial intelligence and its implications for our understanding of human intelligence, citing the likes of Alan Turing and Marvin Minsky as well as contemporary discussions of data-driven language models.

Gwo-Jen Hwang and Nian-Shing Chen, “ Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions ,” Educational Technology & Society 26, no. 2 (2023).

Gwo-Jen Hwang and Nian-Shing Chen are enthusiastic about the potential benefits of incorporating generative AI into education. They outline a variety of roles a large language model like ChatGPT might play, from student to tutor to peer to domain expert to administrator. For example, educators might assign students to “teach” ChatGPT on a subject. Hwang and Chen provide sample ChatGPT session transcripts to illustrate their suggestions. They share prompting techniques to help educators better design AI-based teaching strategies. At the same time, they are concerned about student overreliance on generative AI. They urge educators to guide students to use it critically and to reflect on their interactions with AI. Hwang and Chen don’t touch on concerns about bias, inaccuracy, or fabrication, but they call for further research into the impact of integrating generative AI on learning outcomes.

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Lauren Goodlad and Samuel Baker, “ Now the Humanities Can Disrupt ‘AI’ ,” Public Books (February 20, 2023).

Lauren Goodlad and Samuel Baker situate both academic integrity concerns and the pressures on educators to “embrace” AI in the context of market forces. They ground their discussion of AI risks in a deep technical understanding of the limits of predictive models at mimicking human intelligence. Goodlad and Baker urge educators to communicate the purpose and value of teaching with writing to help students engage with the plurality of the world and communicate with others. Beyond the classroom, they argue, educators should question tech industry narratives and participate in public discussion on regulation and the future of AI. They see higher education as resilient: academic skepticism about former waves of hype around MOOCs, for example, suggests that educators will not likely be dazzled or terrified into submission to AI. Goodlad and Baker hope we will instead take up our place as experts who should help shape the future of the role of machines in human thought and communication.

Kathryn Conrad, “ Sneak Preview: A Blueprint for an AI Bill of Rights for Education ,” Critical AI 2.1 (July 17, 2023).

How can the field of education put the needs of students and scholars first as we shape our response to AI, the way we teach about it, and the way we might incorporate it into pedagogy? Kathryn Conrad’s manifesto builds on and extends the Biden administration’s Office of Science and Technology Policy 2022 “Blueprint for an AI Bill of Rights.” Conrad argues that educators should have input into institutional policies on AI and access to professional development around AI. Instructors should be able to decide whether and how to incorporate AI into pedagogy, basing their decisions on expert recommendations and peer-reviewed research. Conrad outlines student rights around AI systems, including the right to know when AI is being used to evaluate them and the right to request alternate human evaluation. They deserve detailed instructor guidance on policies around AI use without fear of reprisals. Conrad maintains that students should be able to appeal any charges of academic misconduct involving AI, and they should be offered alternatives to any AI-based assignments that might put their creative work at risk of exposure or use without compensation. Both students’ and educators’ legal rights must be respected in any educational application of automated generative systems.

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Essentials of Research Methods in Education 1st Edition

Purchase options and add-ons.

• ISBN-10 1529791138
• ISBN-13 978-1529791136
• Edition 1st
• Publisher SAGE Publications Ltd
• Publication date May 23, 2023
• Language English
• Dimensions 7.32 x 1 x 9.13 inches
• Print length 440 pages
• See all details

Editorial Reviews

This is the text that students have been waiting for. It is comprehensive, reader friendly, and interdisciplinary. The authors frame research as a quest for the truth, and provide specific stages and procedures to assist this search.

This book is written by authors well versed in the challenges of research and it shows the moment you start to read it. The text is clear and to the point with some nice touches of humour. Layout is extremely clear making the book easy to follow and to dip into, and has very useful sections such as "lessons learned the hard way" in each chapter. It also manages to share the energy and enthusiasm for research and its transformational ability.

′This book deals honestly and clearly with the myriad of ideas that students come across when they begin educational research. It is a ′dip in′ book in which students can clarify the concepts they come across in other books and in lectures. Recommended to everyone from undergraduate to doctoral level.′

This book provides a richly comprehensive guide to conducting educational research. The reader is supported in building a deep understanding that offers greater insight and avoids the ‘myth and mystery’ so often associated with the research process. Throughout, an illustrative quest allegory entertains and enlightens the reader without distracting from the rigour of the central purpose. For more experienced researchers Buckler & Moore succeed in making the familiar strange. Thoroughly recommended.

About the Author

Scott Buckler has been involved in education since the 1990s, fluctuating between primary teaching, secondary teaching (science, computing, psychology), and universities (education, sport, psychology). From teaching research methods across the expanse of education (from the primary years through to doctorates), Scott has been an advocate of high quality research, through facilitating an open mind while maintaining academic integrity.

His research has encompassed many areas, often with the theme of personal and professional growth, through the lens of transpersonal psychology. His PhD thesis was interdisciplinary, combining anthropology and psychology to explore the way that the martial arts lead to personal transformation. Professionally, Scott’s research is predominantly in applied educational psychology, inclusive education, and research methods.

Scott is a Chartered Teacher and Chartered Psychologist.

Harriett Moore has a varied background within the field of both education and research.  She studied animal behaviour at University College Chester (a college of Liverpool University) where she engaged with a wide selection of research methodologies, from observational approaches to applied research in a range of contexts. Her skills have transferred effectively into analysing human behaviour.

Harriett has been involved with education since the mid-2000s as a secondary teacher, IT Operations Manager, among other roles. Throughout her career, Harriett has engaged with applied research to help facilitate change and to inform a variety of audiences, continually challenging perspectives in the limitations of what people think is possible, and what can actually be achieved.

Harriett currently manages the school’s Duke of Edinburgh Award Scheme and is a firm believer that education is much more than classroom based learning, rather requiring a “whole-person centred” approach. Her current research projects include teacher wellbeing, martial arts within the school setting, and student/staff perceptions on elearning.

Product details

• Publisher ‏ : ‎ SAGE Publications Ltd; 1st edition (May 23, 2023)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 440 pages
• ISBN-10 ‏ : ‎ 1529791138
• ISBN-13 ‏ : ‎ 978-1529791136
• Item Weight ‏ : ‎ 1.75 pounds
• Dimensions ‏ : ‎ 7.32 x 1 x 9.13 inches
• #2,789 in Education Research (Books)
• #25,487 in Education (Books)

About the authors

Harriett moore.

Harriett Moore has a varied background within the field of both education and research. She studied animal behaviour at University College Chester (a college of Liverpool University) where she engaged with a wide selection of research methodologies, from observational approaches to applied research in a range of contexts. Her skills have transferred effectively into analysing human behaviour.

Scott Buckler

Scott has an extensive career in education, as a primary and secondary school teacher, elearning developer, and as a principal lecturer, having worked for four universities predominantly in education, psychology and inclusion. Scott has led degree programmes from undergraduate to doctoral level, and lectured predominantly on applied educational psychology, research methods, elearning and leadership.

Scott has a PhD in anthropology and is widely published in the areas of psychology and education. He is a Chartered Teacher and a Chartered Psychologist with expertise in transpersonal psychology. In recent years, Scott has returned to schools given his belief that to work and write in the academic context of education, school experience needs to be both recent and relevant.

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