news article about new normal education using printed media

Print books or e-books? In the new normal education system, which one is more beneficial?

Is digital learning the beginning of the end for printed textbooks.

In our pre-pandemic times, studying for many Filipino youth involved getting their noses buried inside the pages of a book. Those bounded pieces of paper have been the sword and shield of many students through the years, and these have given parents assurances that their kids are being fed with the right knowledge.

But as the entire planet went to a COVID-19 shift, so did our way of learning. Virtual education paved the way for many to continue learning while the battle against the virus raged on. New materials are introduced in the digital learning system, making e-books among the new sources for knowledge. While the internet has been a dependable partner for students even during the days prior to the pandemic, the question many ask is: Is digital learning the beginning of the end for printed textbooks?

For learning materials provider Rex Education, giving students more available learning resources in a safe manner is a must these days. That's why it has expanded its offerings of printed textbooks with e-book versions and various digital complimentary learning and assessment materials. Its goal is not to replace printed books, but to create more options suitable for the varying needs and circumstances of the Filipino Whole Learners that it serves.

The pros and cons of e-books

As digital natives, students now are more at ease with e-books. One of their benefits is their portability. One device can hold a library of books without weighing more than one encyclopedia.

While it is becoming the best option in today's setup, e-books also have their own set of limitations and weaknesses. The biggest of which are digital fatigue and distraction. With more time exposed to digital devices, learning these days have become quite unhealthy.

"The amount of screen time for elementary students aged six to 12 should only be up to 90 minutes a day. For secondary school students aged 13 to 17, the recommended screen time should not be more than two hours per day," say Rex Education. "That recommended number is easily surpassed when classes are held online and assignments require online research, and the learning materials they have access to are digital as well. The additional exposure to screen time definitely increases the students’ susceptibility to screen fatigue, which may lead to blurred vision, redness, dryness, and irritation."

Apart from the prolonged screen time, devices such as tablets and laptops also hold more distraction to students with the help of entertainment and gaming apps, and other digital sites.

"People who read e-books tend to get sidetracked more easily, but not just because the internet is right at their fingertips," Rex Education states. "Digital readers tend to spend more time scanning for keywords than actually processing what they’re reading. It’s easy to get distracted by links and get sucked into an internet rabbit hole of irrelevant—and sometimes, dangerous—content on the web."

The value of printed textbooks

For decades, print books have been the top choice as learning material due to it being less strenuous on the eyes and providing a more tangible experience for the reader. And when it comes to the retention ability and learning experience between e-books and printed books, printed books have been found to reign supreme.

A study led by Anne Mangen of Norway's Stavanger University shows that readers of print books were found to absorb and remember more of the material that they were reading compared to e-book or Kindle readers. This makes students who have books at home also more likely to score higher on tests.

"In this study, we found that paper readers did report higher on measures having to do with empathy and transportation and immersion, and narrative coherence, than iPad readers," Mangen tells to The Guardian.

Researchers believe this is because having books at home encourages children to read for fun and talk to their parents about what they’ve learned, which only stands to benefit them in class.

"Compared to e-books, printed books present not distraction, but imagination," the learning materials provider says. "Books provide gateways to unlocking the capabilities of the brain, encouraging the learner to put the things they learn together, therefore enabling better learning retention. While books continue to be found better for a student’s learning experience, the pandemic has made it challenging for students and parents to purchase print books. Required textbook sets were bulky, needed to be traveled, and required a significant amount of storage in the home."

The new normal of learning materials

To balance the strengths and weaknesses of both printed and digital books, Rex Education has made it its responsibility to offer as many options as it can to match the varying needs of the students—both printed and digital.

"As schools implement different models of distance learning, it is important for us to be more inclusive and flexible in providing access to quality and relevant learning materials. Since schools may be serving students with different setups at home or even from different locations, providing the option of both digital and printed books makes it easier for students to choose which learning material suits their needs," says Don Timothy Buhain, chief executive officer of Rex Education. "Rex Education believes that quality education should be accessible to every Filipino Whole Learner—and that is what we always strive to achieve in every printed and digital book that we create."

To date, the learning materials provider has made available a wide suite of printed books and e-books on its digital bookstore to make quality education more accessible to all. Parents, educators, and students can now conveniently browse and shop its huge lineup of learning solutions in print or digital format through www.rexestore.com .

"Technology will never replace good parenting and good teachers. So when you read to your child—regardless of whether it’s a traditional or electronic book—keep the conversation lively. Talk about what he sees on the page. Ask what he thinks will happen next. Because as researchers and educators all agree, the most important app, especially for little kids, is real human support," it ends.

The new normal in U.S. schools is unsustainable–and inaction could cost $28 trillion

More than three years after the pandemic closed schools across the country, the public consciousness has largely moved on, but our education system remains buffeted by urgent needs, shifting priorities, conflicting funding mandates, and deep political divisions. The new normal is anything but normal.

Learning loss, poor student mental health, teacher shortages, and the rapid pace of technological change are powerful forces that will shape the education sector for years to come. Stanford University economist Eric Hanushek estimates the lasting societal costs of the pandemic’s effects on students could amount to more than $28 trillion over the rest of this century.

The White House recently called for an all-hands-on-deck approach to fighting learning loss while the nation nervously awaits this year’s NAEP scores which last year were the lowest in two decades in reading and math.

3 seemingly insurmountable challenges

The impacts of the pandemic were unequally distributed . In some districts, students lost nearly two full grade levels while in others, math scores were almost unchanged. Three factors–access to broadband, whether a student’s parents were able to hold a job through remote work, and whether a student experienced a COVID-related death in their family–were associated with higher rates of learning loss, and highly correlated with lower income levels.

If learning loss was not troubling enough, CDC data reveals that 37% of high school students struggled with mental health issues during the pandemic. The rates are even more alarming for girls: three in five reported persistent sadness with one in three even considering suicide. The White House recently announced that rates of chronic absenteeism have doubled since the pandemic, due in part to mental health and behavioral challenges. Students struggling with mental health issues are twice as likely to drop out.

At the same time that students are struggling, teachers are also under pressure. Teacher turnover has gone up since the end of the pandemic. The response in some states has been to dramatically relax credentialing standards. Today, approximately one in 10 positions are either unfilled or held by someone without the proper certification and that number can be 4x higher in lower-income schools in rural and urban districts.

The missing piece

Numerous studies have shown the quality of the classroom teacher to be the single most important factor impacting student success. Uncertified teachers also exit the field at high rates, perpetuating the shortage. With the number of graduates from traditional schools of education declining, alternative pathways to certification are the only viable path to addressing the shortage. Mid-career professionals gain training in the areas they lack while coaching, mentorship, and accredited credentials protect teaching standards. Alternative pathways have also proven to be the best path to finding teachers in the hardest-to-fill areas of STEM and special ed while boosting teacher diversity.

With an insufficient supply of certified teachers, it is all the more challenging to keep pace with technological change. Since the release of ChatGPT and the large language model-based chatbots, education sector stakeholders have been scrambling to sort out the hype from reality.

Powerful chatbots can potentially do everything from preparing course catalogs to developing quizzes for administrators and educators to researching term papers for students. The key will be to arm students with the knowledge to harness these tools while also protecting student privacy and combatting the advance of even more pernicious forms of cyberbullying and disinformation.

The promise of education technology has always been to boost learner engagement at scale with software that could adapt to the needs of an individual learner. Now is the time for all stakeholders–educators, policymakers, and entrepreneurs–to lean into the opportunity. As students prepare for the workforce, generative AI and other sweeping technological changes present opportunities for greater productivity but also the challenge of accelerating workforce dislocations.

Education technology holds the promise to transform not only educational systems but also entire economies. Effecting change at scale will take thoughtful investment, backed by rigorous research, timely data, and a tactical understanding of the shifting education trends that will impact the sector for years to come.

John Rogers is a Partner at TPG’s Rise Fund, the world’s largest social impact fund .

More must-read commentary published by  Fortune :

• The ‘Big Stay’ isn’t going away as the labor market stops rewarding job hoppers, according to  ADP payroll data
• Freakonomics author: ‘Objections to  data science in K-12 education  make no sense’
• Why  boomers are catching up with AI faster than Gen Zers , according to Microsoft’s modern work lead
• The growing case for doing less: How  harmless cancers are being overdiagnosed  in America

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of  Fortune .

Latest in Commentary

• 0 minutes ago

More Americans are working past age 65—and that’s good news for employers

Scientists inspired the right guardrails for nuclear energy, the internet, and DNA research. Let them do the same for AI

Burned out and underappreciated, women’s career advancement had stalled long before the anti-DEI backlash

A new Cold War is brewing at sea–and the West’s security and prosperity are at stake

The FTC noncompete ruling will narrow the gender gap in entrepreneurship

The race for human-AI interaction usage data is on—and the stakes are high

Most popular.

‘Americans just work harder’ than Europeans, says CEO of Norway’s $1.6 trillion oil fund, because they have a higher ‘general level of ambition’

Amazon should be forced to disclose how Jeff Bezos and others were instructed to use the Signal disappearing-message app, FTC says

On a crucial earnings call, Musk reminds the world Tesla is a tech company. ‘Even if I’m kidnapped by aliens tomorrow, Tesla will solve autonomy’

Ryanair CEO dishes advice to Boeing on managing its crises: ‘Never put a pilot in charge of an airline’

A 60-year-old worker in Texas says she’s dependent on apps that let her get paid early: ‘They get you hooked on having that money’

Jamie Dimon says America needs to ‘take a deep breath’ before facing off with China, because the U.S. is actually in a ‘very good position’ to negotiate

• Toggle Accessibility Statement
• Skip to Main Content

DepEd prepares Self-Learning Modules for education’s new normal

July 1, 2020 — Steadfast in its preparation for School Year 2020-2021, the Department of Education (DepEd) will provide Self-Learning Modules (SLMs) with the alternative learning delivery modalities to be offered for various types of learners across the Philippines.

The integration of SLMs with the alternative learning delivery modalities (modular, television-based, radio-based instruction, blended, and online) will help DepEd ensure that all learners have access to quality basic education for SY 2020-2021 with face-to-face classes still prohibited due to the public health situation.

“The SLMs and the other alternative learning delivery modalities are in place to address the needs, situations, and resources of each and every learner and will cover all the bases in ensuring that basic education will be accessible amid the present crisis posed by COVID-19,” DepEd Secretary Leonor Briones said.

SLMs are delivered in printed format to schools that are located in coastal areas, far-flung provinces, and communities without access to the internet or electricity. For households with gadgets and devices, the Department has announced that SLMs can also be accessed online or offline.

Secretary Briones noted that SLMs will be integrated in video lessons, most especially for K to 3 learners who will require more auditory learning than other grade levels.

With inclusivity in mind, DepEd Region II Director Dr. Estela Carino added that learners with special needs will have video sessions as well as assigned teachers that will be guiding them throughout their lessons.

“The activities we placed in the SLMs will be appropriate for learners with special needs, too. We still have to give these learners the same kind of care that we gave them while we were doing face-to-face classes. Most of them would be using video-taped lessons aside from the modules,” RD Carino said.

DepEd has provided a set of SLMs for each region for contextualization, which shall be printed in July and will be prepared for distribution nationwide, including learners in coastal and far-flung areas.

The Department also assured that the safety and health of teachers and personnel will be its top priority as SLMs can be done at home. Teachers who would need to visit their schools to get materials to prepare the SLMs are required to follow the existing work arrangement and health protocols.

To further integrate the SLMs with the learning delivery modalities, DepEd is set to finalize the learning delivery modalities which will be implemented for each region after the consolidation of Learner Enrollment and Survey Forms (LESF) from the June enrollment.

• Research article
• Open access
• Published: 15 February 2018

Blended learning: the new normal and emerging technologies

• Charles Dziuban 1 ,
• Charles R. Graham 2 ,
• Patsy D. Moskal   ORCID: orcid.org/0000-0001-6376-839X 1 ,
• Anders Norberg 3 &
• Nicole Sicilia 1  

International Journal of Educational Technology in Higher Education volume  15 , Article number:  3 ( 2018 ) Cite this article

549k Accesses

354 Citations

118 Altmetric

Metrics details

This study addressed several outcomes, implications, and possible future directions for blended learning (BL) in higher education in a world where information communication technologies (ICTs) increasingly communicate with each other. In considering effectiveness, the authors contend that BL coalesces around access, success, and students’ perception of their learning environments. Success and withdrawal rates for face-to-face and online courses are compared to those for BL as they interact with minority status. Investigation of student perception about course excellence revealed the existence of robust if-then decision rules for determining how students evaluate their educational experiences. Those rules were independent of course modality, perceived content relevance, and expected grade. The authors conclude that although blended learning preceded modern instructional technologies, its evolution will be inextricably bound to contemporary information communication technologies that are approximating some aspects of human thought processes.

Introduction

Blended learning and research issues.

Blended learning (BL), or the integration of face-to-face and online instruction (Graham 2013 ), is widely adopted across higher education with some scholars referring to it as the “new traditional model” (Ross and Gage 2006 , p. 167) or the “new normal” in course delivery (Norberg et al. 2011 , p. 207). However, tracking the accurate extent of its growth has been challenging because of definitional ambiguity (Oliver and Trigwell 2005 ), combined with institutions’ inability to track an innovative practice, that in many instances has emerged organically. One early nationwide study sponsored by the Sloan Consortium (now the Online Learning Consortium) found that 65.2% of participating institutions of higher education (IHEs) offered blended (also termed hybrid ) courses (Allen and Seaman 2003 ). A 2008 study, commissioned by the U.S. Department of Education to explore distance education in the U.S., defined BL as “a combination of online and in-class instruction with reduced in-class seat time for students ” (Lewis and Parsad 2008 , p. 1, emphasis added). Using this definition, the study found that 35% of higher education institutions offered blended courses, and that 12% of the 12.2 million documented distance education enrollments were in blended courses.

The 2017 New Media Consortium Horizon Report found that blended learning designs were one of the short term forces driving technology adoption in higher education in the next 1–2 years (Adams Becker et al. 2017 ). Also, blended learning is one of the key issues in teaching and learning in the EDUCAUSE Learning Initiative’s 2017 annual survey of higher education (EDUCAUSE 2017 ). As institutions begin to examine BL instruction, there is a growing research interest in exploring the implications for both faculty and students. This modality is creating a community of practice built on a singular and pervasive research question, “How is blended learning impacting the teaching and learning environment?” That question continues to gain traction as investigators study the complexities of how BL interacts with cognitive, affective, and behavioral components of student behavior, and examine its transformation potential for the academy. Those issues are so compelling that several volumes have been dedicated to assembling the research on how blended learning can be better understood (Dziuban et al. 2016 ; Picciano et al. 2014 ; Picciano and Dziuban 2007 ; Bonk and Graham 2007 ; Kitchenham 2011 ; Jean-François 2013 ; Garrison and Vaughan 2013 ) and at least one organization, the Online Learning Consortium, sponsored an annual conference solely dedicated to blended learning at all levels of education and training (2004–2015). These initiatives address blended learning in a wide variety of situations. For instance, the contexts range over K-12 education, industrial and military training, conceptual frameworks, transformational potential, authentic assessment, and new research models. Further, many of these resources address students’ access, success, withdrawal, and perception of the degree to which blended learning provides an effective learning environment.

Currently the United States faces a widening educational gap between our underserved student population and those communities with greater financial and technological resources (Williams 2016 ). Equal access to education is a critical need, one that is particularly important for those in our underserved communities. Can blended learning help increase access thereby alleviating some of the issues faced by our lower income students while resulting in improved educational equality? Although most indicators suggest “yes” (Dziuban et al. 2004 ), it seems that, at the moment, the answer is still “to be determined.” Quality education presents a challenge, evidenced by many definitions of what constitutes its fundamental components (Pirsig 1974 ; Arum et al. 2016 ). Although progress has been made by initiatives, such as, Quality Matters ( 2016 ), the OLC OSCQR Course Design Review Scorecard developed by Open SUNY (Open SUNY n.d. ), the Quality Scorecard for Blended Learning Programs (Online Learning Consortium n.d. ), and SERVQUAL (Alhabeeb 2015 ), the issue is by no means resolved. Generally, we still make quality education a perceptual phenomenon where we ascribe that attribute to a course, educational program, or idea, but struggle with precisely why we reached that decision. Searle ( 2015 ), summarizes the problem concisely arguing that quality does not exist independently, but is entirely observer dependent. Pirsig ( 1974 ) in his iconic volume on the nature of quality frames the context this way,

“There is such thing as Quality, but that as soon as you try to define it, something goes haywire. You can’t do it” (p. 91).

Therefore, attempting to formulate a semantic definition of quality education with syntax-based metrics results in what O’Neil (O'Neil 2017 ) terms surrogate models that are rough approximations and oversimplified. Further, the derived metrics tend to morph into goals or benchmarks, losing their original measurement properties (Goodhart 1975 ).

Information communication technologies in society and education

Blended learning forces us to consider the characteristics of digital technology, in general, and information communication technologies (ICTs), more specifically. Floridi ( 2014 ) suggests an answer proffered by Alan Turing: that digital ICTs can process information on their own, in some sense just as humans and other biological life. ICTs can also communicate information to each other, without human intervention, but as linked processes designed by humans. We have evolved to the point where humans are not always “in the loop” of technology, but should be “on the loop” (Floridi 2014 , p. 30), designing and adapting the process. We perceive our world more and more in informational terms, and not primarily as physical entities (Floridi 2008 ). Increasingly, the educational world is dominated by information and our economies rest primarily on that asset. So our world is also blended, and it is blended so much that we hardly see the individual components of the blend any longer. Floridi ( 2014 ) argues that the world has become an “infosphere” (like biosphere) where we live as “inforgs.” What is real for us is shifting from the physical and unchangeable to those things with which we can interact.

Floridi also helps us to identify the next blend in education, involving ICTs, or specialized artificial intelligence (Floridi 2014 , 25; Norberg 2017 , 65). Learning analytics, adaptive learning, calibrated peer review, and automated essay scoring (Balfour 2013 ) are advanced processes that, provided they are good interfaces, can work well with the teacher— allowing him or her to concentrate on human attributes such as being caring, creative, and engaging in problem-solving. This can, of course, as with all technical advancements, be used to save resources and augment the role of the teacher. For instance, if artificial intelligence can be used to work along with teachers, allowing them more time for personal feedback and mentoring with students, then, we will have made a transformational breakthrough. The Edinburg University manifesto for teaching online says bravely, “Automation need not impoverish education – we welcome our robot colleagues” (Bayne et al. 2016 ). If used wisely, they will teach us more about ourselves, and about what is truly human in education. This emerging blend will also affect curricular and policy questions, such as the what? and what for? The new normal for education will be in perpetual flux. Floridi’s ( 2014 ) philosophy offers us tools to understand and be in control and not just sit by and watch what happens. In many respects, he has addressed the new normal for blended learning.

Literature of blended learning

A number of investigators have assembled a comprehensive agenda of transformative and innovative research issues for blended learning that have the potential to enhance effectiveness (Garrison and Kanuka 2004 ; Picciano 2009 ). Generally, research has found that BL results in improvement in student success and satisfaction, (Dziuban and Moskal 2011 ; Dziuban et al. 2011 ; Means et al. 2013 ) as well as an improvement in students’ sense of community (Rovai and Jordan 2004 ) when compared with face-to-face courses. Those who have been most successful at blended learning initiatives stress the importance of institutional support for course redesign and planning (Moskal et al. 2013 ; Dringus and Seagull 2015 ; Picciano 2009 ; Tynan et al. 2015 ). The evolving research questions found in the literature are long and demanding, with varied definitions of what constitutes “blended learning,” facilitating the need for continued and in-depth research on instructional models and support needed to maximize achievement and success (Dringus and Seagull 2015 ; Bloemer and Swan 2015 ).

Educational access

The lack of access to educational technologies and innovations (sometimes termed the digital divide) continues to be a challenge with novel educational technologies (Fairlie 2004 ; Jones et al. 2009 ). One of the promises of online technologies is that they can increase access to nontraditional and underserved students by bringing a host of educational resources and experiences to those who may have limited access to on-campus-only higher education. A 2010 U.S. report shows that students with low socioeconomic status are less likely to obtain higher levels of postsecondary education (Aud et al. 2010 ). However, the increasing availability of distance education has provided educational opportunities to millions (Lewis and Parsad 2008 ; Allen et al. 2016 ). Additionally, an emphasis on open educational resources (OER) in recent years has resulted in significant cost reductions without diminishing student performance outcomes (Robinson et al. 2014 ; Fischer et al. 2015 ; Hilton et al. 2016 ).

Unfortunately, the benefits of access may not be experienced evenly across demographic groups. A 2015 study found that Hispanic and Black STEM majors were significantly less likely to take online courses even when controlling for academic preparation, socioeconomic status (SES), citizenship, and English as a second language (ESL) status (Wladis et al. 2015 ). Also, questions have been raised about whether the additional access afforded by online technologies has actually resulted in improved outcomes for underserved populations. A distance education report in California found that all ethnic minorities (except Asian/Pacific Islanders) completed distance education courses at a lower rate than the ethnic majority (California Community Colleges Chancellor’s Office 2013 ). Shea and Bidjerano ( 2014 , 2016 ) found that African American community college students who took distance education courses completed degrees at significantly lower rates than those who did not take distance education courses. On the other hand, a study of success factors in K-12 online learning found that for ethnic minorities, only 1 out of 15 courses had significant gaps in student test scores (Liu and Cavanaugh 2011 ). More research needs to be conducted, examining access and success rates for different populations, when it comes to learning in different modalities, including fully online and blended learning environments.

Framing a treatment effect

Over the last decade, there have been at least five meta-analyses that have addressed the impact of blended learning environments and its relationship to learning effectiveness (Zhao et al. 2005 ; Sitzmann et al. 2006 ; Bernard et al. 2009 ; Means et al. 2010 , 2013 ; Bernard et al. 2014 ). Each of these studies has found small to moderate positive effect sizes in favor of blended learning when compared to fully online or traditional face-to-face environments. However, there are several considerations inherent in these studies that impact our understanding the generalizability of outcomes.

Dziuban and colleagues (Dziuban et al. 2015 ) analyzed the meta-analyses conducted by Means and her colleagues (Means et al. 2013 ; Means et al. 2010 ), concluding that their methods were impressive as evidenced by exhaustive study inclusion criteria and the use of scale-free effect size indices. The conclusion, in both papers, was that there was a modest difference in multiple outcome measures for courses featuring online modalities—in particular, blended courses. However, with blended learning especially, there are some concerns with these kinds of studies. First, the effect sizes are based on the linear hypothesis testing model with the underlying assumption that the treatment and the error terms are uncorrelated, indicating that there is nothing else going on in the blending that might confound the results. Although the blended learning articles (Means et al. 2010 ) were carefully vetted, the assumption of independence is tenuous at best so that these meta-analysis studies must be interpreted with extreme caution.

There is an additional concern with blended learning as well. Blends are not equivalent because of the manner on which they are configured. For instance, a careful reading of the sources used in the Means, et al. papers will identify, at minimum, the following blending techniques: laboratory assessments, online instruction, e-mail, class web sites, computer laboratories, mapping and scaffolding tools, computer clusters, interactive presentations and e-mail, handwriting capture, evidence-based practice, electronic portfolios, learning management systems, and virtual apparatuses. These are not equivalent ways in which to configure courses, and such nonequivalence constitutes the confounding we describe. We argue here that, in actuality, blended learning is a general construct in the form of a boundary object (Star and Griesemer 1989 ) rather than a treatment effect in the statistical sense. That is, an idea or concept that can support a community of practice, but is weakly defined fostering disagreement in the general group. Conversely, it is stronger in individual constituencies. For instance, content disciplines (i.e. education, rhetoric, optics, mathematics, and philosophy) formulate a more precise definition because of commonly embraced teaching and learning principles. Quite simply, the situation is more complicated than that, as Leonard Smith ( 2007 ) says after Tolstoy,

“All linear models resemble each other, each non nonlinear system is unique in its own way” (p. 33).

This by no means invalidates these studies, but effect size associated with blended learning should be interpreted with caution where the impact is evaluated within a particular learning context.

Study objectives

This study addressed student access by examining success and withdrawal rates in the blended learning courses by comparing them to face-to-face and online modalities over an extended time period at the University of Central Florida. Further, the investigators sought to assess the differences in those success and withdrawal rates with the minority status of students. Secondly, the investigators examined the student end-of-course ratings of blended learning and other modalities by attempting to develop robust if-then decision rules about what characteristics of classes and instructors lead students to assign an “excellent” value to their educational experience. Because of the high stakes nature of these student ratings toward faculty promotion, awards, and tenure, they act as a surrogate measure for instructional quality. Next, the investigators determined the conditional probabilities for students conforming to the identified rule cross-referenced by expected grade, the degree to which they desired to take the course, and course modality.

Student grades by course modality were recoded into a binary variable with C or higher assigned a value of 1, and remaining values a 0. This was a declassification process that sacrificed some specificity but compensated for confirmation bias associated with disparate departmental policies regarding grade assignment. At the measurement level this was an “on track to graduation index” for students. Withdrawal was similarly coded by the presence or absence of its occurrence. In each case, the percentage of students succeeding or withdrawing from blended, online or face-to-face courses was calculated by minority and non-minority status for the fall 2014 through fall 2015 semesters.

Next, a classification and regression tree (CART) analysis (Brieman et al. 1984 ) was performed on the student end-of-course evaluation protocol ( Appendix 1 ). The dependent measure was a binary variable indicating whether or not a student assigned an overall rating of excellent to his or her course experience. The independent measures in the study were: the remaining eight rating items on the protocol, college membership, and course level (lower undergraduate, upper undergraduate, and graduate). Decision trees are efficient procedures for achieving effective solutions in studies such as this because with missing values imputation may be avoided with procedures such as floating methods and the surrogate formation (Brieman et al. 1984 , Olshen et al. 1995 ). For example, a logistic regression method cannot efficiently handle all variables under consideration. There are 10 independent variables involved here; one variable has three levels, another has nine, and eight have five levels each. This means the logistic regression model must incorporate more than 50 dummy variables and an excessively large number of two-way interactions. However, the decision-tree method can perform this analysis very efficiently, permitting the investigator to consider higher order interactions. Even more importantly, decision trees represent appropriate methods in this situation because many of the variables are ordinally scaled. Although numerical values can be assigned to each category, those values are not unique. However, decision trees incorporate the ordinal component of the variables to obtain a solution. The rules derived from decision trees have an if-then structure that is readily understandable. The accuracy of these rules can be assessed with percentages of correct classification or odds-ratios that are easily understood. The procedure produces tree-like rule structures that predict outcomes.

The model-building procedure for predicting overall instructor rating

For this study, the investigators used the CART method (Brieman et al. 1984 ) executed with SPSS 23 (IBM Corp 2015 ). Because of its strong variance-sharing tendencies with the other variables, the dependent measure for the analysis was the rating on the item Overall Rating of the Instructor , with the previously mentioned indicator variables (college, course level, and the remaining 8 questions) on the instrument. Tree methods are recursive, and bisect data into subgroups called nodes or leaves. CART analysis bases itself on: data splitting, pruning, and homogeneous assessment.

Splitting the data into two (binary) subsets comprises the first stage of the process. CART continues to split the data until the frequencies in each subset are either very small or all observations in a subset belong to one category (e.g., all observations in a subset have the same rating). Usually the growing stage results in too many terminate nodes for the model to be useful. CART solves this problem using pruning methods that reduce the dimensionality of the system.

The final stage of the analysis involves assessing homogeneousness in growing and pruning the tree. One way to accomplish this is to compute the misclassification rates. For example, a rule that produces a .95 probability that an instructor will receive an excellent rating has an associated error of 5.0%.

Implications for using decision trees

Although decision-tree techniques are effective for analyzing datasets such as this, the reader should be aware of certain limitations. For example, since trees use ranks to analyze both ordinal and interval variables, information can be lost. However, the most serious weakness of decision tree analysis is that the results can be unstable because small initial variations can lead to substantially different solutions.

For this study model, these problems were addressed with the k-fold cross-validation process. Initially the dataset was partitioned randomly into 10 subsets with an approximately equal number of records in each subset. Each cohort is used as a test partition, and the remaining subsets are combined to complete the function. This produces 10 models that are all trained on different subsets of the original dataset and where each has been used as the test partition one time only.

Although computationally dense, CART was selected as the analysis model for a number of reasons— primarily because it provides easily interpretable rules that readers will be able evaluate in their particular contexts. Unlike many other multivariate procedures that are even more sensitive to initial estimates and require a good deal of statistical sophistication for interpretation, CART has an intuitive resonance with researcher consumers. The overriding objective of our choice of analysis methods was to facilitate readers’ concentration on our outcomes rather than having to rely on our interpretation of the results.

Institution-level evaluation: Success and withdrawal

The University of Central Florida (UCF) began a longitudinal impact study of their online and blended courses at the start of the distributed learning initiative in 1996. The collection of similar data across multiple semesters and academic years has allowed UCF to monitor trends, assess any issues that may arise, and provide continual support for both faculty and students across varying demographics. Table  1 illustrates the overall success rates in blended, online and face-to-face courses, while also reporting their variability across minority and non-minority demographics.

While success (A, B, or C grade) is not a direct reflection of learning outcomes, this overview does provide an institutional level indication of progress and possible issues of concern. BL has a slight advantage when looking at overall success and withdrawal rates. This varies by discipline and course, but generally UCF’s blended modality has evolved to be the best of both worlds, providing an opportunity for optimizing face-to-face instruction through the effective use of online components. These gains hold true across minority status. Reducing on-ground time also addresses issues that impact both students and faculty such as parking and time to reach class. In addition, UCF requires faculty to go through faculty development tailored to teaching in either blended or online modalities. This 8-week faculty development course is designed to model blended learning, encouraging faculty to redesign their course and not merely consider blended learning as a means to move face-to-face instructional modules online (Cobb et al. 2012 ; Lowe 2013 ).

Withdrawal (Table  2 ) from classes impedes students’ success and retention and can result in delayed time to degree, incurred excess credit hour fees, or lost scholarships and financial aid. Although grades are only a surrogate measure for learning, they are a strong predictor of college completion. Therefore, the impact of any new innovation on students’ grades should be a component of any evaluation. Once again, the blended modality is competitive and in some cases results in lower overall withdrawal rates than either fully online or face-to-face courses.

The students’ perceptions of their learning environments

Other potentially high-stakes indicators can be measured to determine the impact of an innovation such as blended learning on the academy. For instance, student satisfaction and attitudes can be measured through data collection protocols, including common student ratings, or student perception of instruction instruments. Given that those ratings often impact faculty evaluation, any negative reflection can derail the successful implementation and scaling of an innovation by disenfranchised instructors. In fact, early online and blended courses created a request by the UCF faculty senate to investigate their impact on faculty ratings as compared to face-to-face sections. The UCF Student Perception of Instruction form is released automatically online through the campus web portal near the end of each semester. Students receive a splash page with a link to each course’s form. Faculty receive a scripted email that they can send to students indicating the time period that the ratings form will be available. The forms close at the beginning of finals week. Faculty receive a summary of their results following the semester end.

The instrument used for this study was developed over a ten year period by the faculty senate of the University of Central Florida, recognizing the evolution of multiple course modalities including blended learning. The process involved input from several constituencies on campus (students, faculty, administrators, instructional designers, and others), in attempt to provide useful formative and summative instructional information to the university community. The final instrument was approved by resolution of the senate and, currently, is used across the university. Students’ rating of their classes and instructors comes with considerable controversy and disagreement with researchers aligning themselves on both sides of the issue. Recently, there have been a number of studies criticizing the process (Uttl et al. 2016 ; Boring et al. 2016 ; & Stark and Freishtat 2014 ). In spite of this discussion, a viable alternative has yet to emerge in higher education. So in the foreseeable future, the process is likely to continue. Therefore, with an implied faculty senate mandate this study was initiated by this team of researchers.

Prior to any analysis of the item responses collected in this campus-wide student sample, the psychometric quality (domain sampling) of the information yielded by the instrument was assessed. Initially, the reliability (internal consistency) was derived using coefficient alpha (Cronbach 1951 ). In addition, Guttman ( 1953 ) developed a theorem about item properties that leads to evidence about the quality of one’s data, demonstrating that as the domain sampling properties of items improve, the inverse of the correlation matrix among items will approach a diagonal. Subsequently, Kaiser and Rice ( 1974 ) developed the measure of sampling adequacy (MSA) that is a function of the Guttman Theorem. The index has an upper bound of one with Kaiser offering some decision rules for interpreting the value of MSA. If the value of the index is in the .80 to .99 range, the investigator has evidence of an excellent domain sample. Values in the .70s signal an acceptable result, and those in the .60s indicate data that are unacceptable. Customarily, the MSA has been used for data assessment prior to the application of any dimensionality assessments. Computation of the MSA value gave the investigators a benchmark for the construct validity of the items in this study. This procedure has been recommended by Dziuban and Shirkey ( 1974 ) prior to any latent dimension analysis and was used with the data obtained for this study. The MSA for the current instrument was .98 suggesting excellent domain sampling properties with an associated alpha reliability coefficient of .97 suggesting superior internal consistency. The psychometric properties of the instrument were excellent with both measures.

The online student ratings form presents an electronic data set each semester. These can be merged across time to create a larger data set of completed ratings for every course across each semester. In addition, captured data includes course identification variables including prefix, number, section and semester, department, college, faculty, and class size. The overall rating of effectiveness is used most heavily by departments and faculty in comparing across courses and modalities (Table  3 ).

The finally derived tree (decision rules) included only three variables—survey items that asked students to rate the instructor’s effectiveness at:

Helping students achieve course objectives,

Creating an environment that helps students learn, and

Communicating ideas and information.

None of the demographic variables associated with the courses contributed to the final model. The final rule specifies that if a student assigns an excellent rating to those three items, irrespective of their status on any other condition, the probability is .99 that an instructor will receive an overall rating of excellent. The converse is true as well. A poor rating on all three of those items will lead to a 99% chance of an instructor receiving an overall rating of poor.

Tables  4 , 5 and 6 present a demonstration of the robustness of the CART rule for variables on which it was not developed: expected course grade, desire to take the course and modality.

In each case, irrespective of the marginal probabilities, those students conforming to the rule have a virtually 100% chance of seeing the course as excellent. For instance, 27% of all students expecting to fail assigned an excellent rating to their courses, but when they conformed to the rule the percentage rose to 97%. The same finding is true when students were asked about their desire to take the course with those who strongly disagreed assigning excellent ratings to their courses 26% of the time. However, for those conforming to the rule, that category rose to 92%. When course modality is considered in the marginal sense, blended learning is rated as the preferred choice. However, from Table  6 we can observe that the rule equates student assessment of their learning experiences. If they conform to the rule, they will see excellence.

This study addressed increasingly important issues of student success, withdrawal and perception of the learning environment across multiple course modalities. Arguably these components form the crux of how we will make more effective decisions about how blended learning configures itself in the new normal. The results reported here indicate that blending maintains or increases access for most student cohorts and produces improved success rates for minority and non-minority students alike. In addition, when students express their beliefs about the effectiveness of their learning environments, blended learning enjoys the number one rank. However, upon more thorough analysis of key elements students view as important in their learning, external and demographic variables have minimal impact on those decisions. For example college (i.e. discipline) membership, course level or modality, expected grade or desire to take a particular course have little to do with their course ratings. The characteristics they view as important relate to clear establishment and progress toward course objectives, creating an effective learning environment and the instructors’ effective communication. If in their view those three elements of a course are satisfied they are virtually guaranteed to evaluate their educational experience as excellent irrespective of most other considerations. While end of course rating protocols are summative the three components have clear formative characteristics in that each one is directly related to effective pedagogy and is responsive to faculty development through units such as the faculty center for teaching and learning. We view these results as encouraging because they offer potential for improving the teaching and learning process in an educational environment that increases the pressure to become more responsive to contemporary student lifestyles.

Clearly, in this study we are dealing with complex adaptive systems that feature the emergent property. That is, their primary agents and their interactions comprise an environment that is more than the linear combination of their individual elements. Blending learning, by interacting with almost every aspect of higher education, provides opportunities and challenges that we are not able to fully anticipate.

This pedagogy alters many assumptions about the most effective way to support the educational environment. For instance, blending, like its counterpart active learning, is a personal and individual phenomenon experienced by students. Therefore, it should not be surprising that much of what we have called blended learning is, in reality, blended teaching that reflects pedagogical arrangements. Actually, the best we can do for assessing impact is to use surrogate measures such as success, grades, results of assessment protocols, and student testimony about their learning experiences. Whether or not such devices are valid indicators remains to be determined. We may be well served, however, by changing our mode of inquiry to blended teaching.

Additionally, as Norberg ( 2017 ) points out, blended learning is not new. The modality dates back, at least, to the medieval period when the technology of textbooks was introduced into the classroom where, traditionally, the professor read to the students from the only existing manuscript. Certainly, like modern technologies, books were disruptive because they altered the teaching and learning paradigm. Blended learning might be considered what Johnson describes as a slow hunch (2010). That is, an idea that evolved over a long period of time, achieving what Kaufmann ( 2000 ) describes as the adjacent possible – a realistic next step occurring in many iterations.

The search for a definition for blended learning has been productive, challenging, and, at times, daunting. The definitional continuum is constrained by Oliver and Trigwell ( 2005 ) castigation of the concept for its imprecise vagueness to Sharpe et al.’s ( 2006 ) notion that its definitional latitude enhances contextual relevance. Both extremes alter boundaries such as time, place, presence, learning hierarchies, and space. The disagreement leads us to conclude that Lakoff’s ( 2012 ) idealized cognitive models i.e. arbitrarily derived concepts (of which blended learning might be one) are necessary if we are to function effectively. However, the strong possibility exists that blended learning, like quality, is observer dependent and may not exist outside of our perceptions of the concept. This, of course, circles back to the problem of assuming that blending is a treatment effect for point hypothesis testing and meta-analysis.

Ultimately, in this article, we have tried to consider theoretical concepts and empirical findings about blended learning and their relationship to the new normal as it evolves. Unfortunately, like unresolved chaotic solutions, we cannot be sure that there is an attractor or that it will be the new normal. That being said, it seems clear that blended learning is the harbinger of substantial change in higher education and will become equally impactful in K-12 schooling and industrial training. Blended learning, because of its flexibility, allows us to maximize many positive education functions. If Floridi ( 2014 ) is correct and we are about to live in an environment where we are on the communication loop rather than in it, our educational future is about to change. However, if our results are correct and not over fit to the University of Central Florida and our theoretical speculations have some validity, the future of blended learning should encourage us about the coming changes.

Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., & Ananthanarayanan, V. (2017). NMC horizon report: 2017 higher Education Edition . Austin: The New Media Consortium.

Google Scholar  

Alhabeeb, A. M. (2015). The quality assessment of the services offered to the students of the College of Education at King Saud University using (SERVQUAL) method. Journal of Education and Practice , 6 (30), 82–93.

Allen, I. E., & Seaman, J. (2003). Sizing the opportunity: The quality and extent of online education in the United States, 2002 and 2003. Retrieved from http://files.eric.ed.gov/fulltext/ED530060.pdf

Allen, I. E., Seaman, J., Poulin, R., & Straut, T. T. (2016). Online report card: Tracking online education in the United States, 1–4. Retrieved from http://onlinelearningsurvey.com/reports/onlinereportcard.pdf

Arum, R., Roksa, J., & Cook, A. (2016). Improving quality in American higher education: Learning outcomes and assessments for the 21st century . San Francisco: Jossey-Bass.

Aud, S., Hussar, W., Planty, M., Snyder, T., Bianco, K., Fox, M. A., & Drake, L. (2010). The condition of education - 2010. Education, 4–29. https://doi.org/10.1037/e492172006-019

Balfour, S. P. (2013). Assessing writing in MOOCs: Automated essay scoring and calibrated peer review. Research and Practice in Assessment , 2013 (8), 40–48.

Bayne, S., Evans, P., Ewins, R.,Knox, J., Lamb, J., McLeod, H., O’Shea, C., Ross, J., Sheail, P. & Sinclair, C, (2016) Manifesto for teaching online. Digital Education at Edinburg University. Retrieved from https://onlineteachingmanifesto.wordpress.com/the-text/

Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research , 79 (3), 1243–1289. https://doi.org/10.3102/0034654309333844 .

Article   Google Scholar  

Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. Journal of Computing in Higher Education , 26 (1), 87–122.

Bloemer, W., & Swan, K. (2015). Investigating informal blending at the University of Illinois Springfield. In A. G. Picciano, C. D. Dziuban, & C. R. Graham (Eds.), Blended learning: Research perspectives , (vol. 2, pp. 52–69). New York: Routledge.

Bonk, C. J., & Graham, C. R. (2007). The handbook of blended learning: Global perspectives, local designs . San Francisco: Pfeiffer.

Boring, A., Ottoboni, K., & Stark, P.B. (2016). Student evaluations of teaching (mostly) do not measure teaching effectiveness. EGERA.

Brieman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees . New York: Chapman & Hall.

California Community Colleges Chancellor’s Office. (2013). Distance education report.

Cobb, C., deNoyelles, A., & Lowe, D. (2012). Influence of reduced seat time on satisfaction and perception of course development goals: A case study in faculty development. The Journal of Asynchronous Learning , 16 (2), 85–98.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika , 16 (3), 297–334 Retrieved from http://psych.colorado.edu/~carey/courses/psyc5112/readings/alpha_cronbach.pdf .

Article   MATH   Google Scholar  

Dringus, L. P., and A. B. Seagull. 2015. A five-year study of sustaining blended learning initiatives to enhance academic engagement in computer and information sciences campus courses. In Blended learning: Research perspectives. Vol. 2. Edited by A. G. Picciano, C. D. Dziuban, and C. R. Graham, 122-140. New York: Routledge.

Dziuban, C. D., & Shirkey, E. C. (1974). When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin , 81(6), 358. https://doi.org/10.1037/h0036316 .

Dziuban, C., Hartman, J., Cavanagh, T., & Moskal, P. (2011). Blended courses as drivers of institutional transformation. In A. Kitchenham (Ed.), Blended learning across disciplines: Models for implementation , (pp. 17–37). Hershey: IGI Global.

Chapter   Google Scholar  

Dziuban, C., & Moskal, P. (2011). A course is a course is a course: Factor invariance in student evaluation of online, blended and face-to-face learning environments. The Internet and Higher Education , 14 (4), 236–241.

Dziuban, C., Moskal, P., Hermsdorfer, A., DeCantis, G., Norberg, A., & Bradford, G., (2015) A deconstruction of blended learning. Presented at the 11 th annual Sloan-C blended learning conference and workshop

Dziuban, C., Picciano, A. G., Graham, C. R., & Moskal, P. D. (2016). Conducting research in online and blended learning environments: New pedagogical frontiers . New York: Routledge, Taylor & Francis Group.

Dziuban, C. D., Hartman, J. L., & Moskal, P. D. (2004). Blended learning. EDUCAUSE Research Bulletin , 7 , 1–12.

EDUCAUSE. (2017) 2017 key issues in teaching & learning. Retrieved from https://www.EDUCAUSE.edu/eli/initiatives/key-issues-in-teaching-and-learning

Fairlie, R. (2004). Race and the digital divide. The B.E. Journal of Economic Analysis & Policy , 3 (1). https://doi.org/10.2202/1538-0645.1263 .

Fischer, L., Hilton, J., Robinson, T. J., & Wiley, D. (2015). A Multi-institutional Study of the Impact of Open Textbook Adoption on the Learning Outcomes of Post-secondary Students . Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-015-9101-x .

Floridi, L. (2008). A defence of informational structural realism. Synthese , 161 (2), 219–253.

Article   MathSciNet   Google Scholar  

Floridi, L. (2014). The 4th revolution: How the infosphere is reshaping human reality . Oxford: Oxford University Press.

Garrison, D. R., & Vaughan, N. D. (2013). Blended learning in higher education , (1st ed., ). San Francisco: Jossey-Bass Print.

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

Goodhart, C.A.E. (1975). “Problems of monetary management: The U.K. experience.” Papers in Monetary Economics. Reserve Bank of Australia. I.

Graham, C. R. (2013). Emerging practice and research in blended learning. In M. G. Moore (Ed.), Handbook of distance education , (3rd ed., pp. 333–350). New York: Routledge.

Guttman, L. (1953). Image theory for the structure of quantitative variates. Psychometrika , 18 , 277–296.

Article   MathSciNet   MATH   Google Scholar  

Hilton, J., Fischer, L., Wiley, D., & Williams, L. (2016). Maintaining momentum toward graduation: OER and the course throughput rate. International Review of Research in Open and Distance Learning , 17 (6) https://doi.org/10.19173/irrodl.v17i6.2686 .

IBM Corp. Released (2015). IBM SPSS statistics for windows, version 23.0 . Armonk: IBM Corp.

Jean-François, E. (2013). Transcultural blended learning and teaching in postsecondary education . Hershey: Information Science Reference.

Book   Google Scholar  

Jones, S., Johnson-Yale, C., Millermaier, S., & Pérez, F. S. (2009). U.S. college students’ internet use: Race, gender and digital divides. Journal of Computer-Mediated Communication , 14 (2), 244–264 https://doi.org/10.1111/j.1083-6101.2009.01439.x .

Kaiser, H. F., & Rice, J. (1974). Little Jiffy, Mark IV. Journal of Educational and Psychological Measurement , 34(1), 111–117.

Kaufmann, S. (2000). Investigations . New York: Oxford University Press.

Kitchenham, A. (2011). Blended learning across disciplines: Models for implementation . Hershey: Information Science Reference.

Lakoff, G. (2012). Women, fire, and dangerous things: What categories reveal about the mind . Chicago: The University of Chicago Press.

Lewis, L., & Parsad, B. (2008). Distance education at degree-granting postsecondary institutions : 2006–07 (NCES 2009–044) . Washington: Retrieved from http://nces.ed.gov/pubs2009/2009044.pdf .

Liu, F., & Cavanaugh, C. (2011). High enrollment course success factors in virtual school: Factors influencing student academic achievement. International Journal on E-Learning , 10 (4), 393–418.

Lowe, D. (2013). Roadmap of a blended learning model for online faculty development. Invited feature article in Distance Education Report , 17 (6), 1–7.

Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record , 115 (3), 1–47.

Means, B., Toyama, Y., Murphy, R., Kaia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning . Washington: US Department of Education.

Moskal, P., Dziuban, C., & Hartman, J. (2013). Blended learning: A dangerous idea? The Internet and Higher Education , 18 , 15–23.

Norberg, A. (2017). From blended learning to learning onlife: ICTs, time and access in higher education (Doctoral dissertation, Umeå University).

Norberg, A., Dziuban, C. D., & Moskal, P. D. (2011). A time-based blended learning model. On the Horizon , 19 (3), 207–216. https://doi.org/10.1108/10748121111163913 .

Oliver, M., & Trigwell, K. (2005). Can ‘blended learning’ be redeemed? e-Learning , 2 (1), 17–25.

Olshen, Stone , Steinberg , and Colla (1995). CART classification and regression trees. Tree-structured nonparametric data analysis. Statistical algorithms. Salford systems interface and documentation. Salford Systems .

O'Neil, C. (2017). Weapons of math destruction: How big data increases inequality and threatens democracy . Broadway Books.

Online Learning Consortium. The OLC quality scorecard for blended learning programs. Retrieved from https://onlinelearningconsortium.org/consult/olc-quality-scorecard-blended-learning-programs/

Open SUNY. The OSCQR course design review scorecard. Retrieved from https://onlinelearningconsortium.org/consult/oscqr-course-design-review/

Picciano, A. G. (2009). Blending with purpose: The multimodal model. Journal of Asynchronous Learning Networks , 13 (1), 7–18.

Picciano, A. G., Dziuban, C., & Graham, C. R. (2014). Blended learning: Research perspectives , (vol. 2). New York: Routledge.

Picciano, A. G., & Dziuban, C. D. (2007). Blended learning: Research perspectives . Needham: The Sloan Consortium.

Pirsig, R. M. (1974). Zen and the art of motorcycle maintenance: An inquiry into values . New York: Morrow.

Quality Matters. (2016). About Quality Matters. Retrieved from https://www.qualitymatters.org/research

Robinson, T. J., Fischer, L., Wiley, D. A., & Hilton, J. (2014). The Impact of Open Textbooks on Secondary Science Learning Outcomes . Educational Researcher. https://doi.org/10.3102/0013189X14550275 .

Ross, B., & Gage, K. (2006). Global perspectives on blended learning: Insight from WebCT and our customers in higher education. In C. J. Bonk, & C. R. Graham (Eds.), Handbook of blended learning: Global perspectives, local designs , (pp. 155–168). San Francisco: Pfeiffer.

Rovai, A. P., & Jordan, H. M. (2004). Blended learning and sense of community: A comparative analysis with traditional and fully online graduate courses. International Review of Research in Open and Distance Learning , 5 (2), 1–13.

Searle, J. R. (2015). Seeing things as they are: A theory of perception . Chicago: Oxford University Press.

Sharpe, R., Benfield, G., Roberts, G., & Francis, R. (2006). The undergraduate experience of blended learning: A review of UK literature and research. The Higher Education Academy, (October 2006).

Shea, P., & Bidjerano, T. (2014). Does online learning impede degree completion? A national study of community college students. Computers and Education , 75 , 103–111 https://doi.org/10.1016/j.compedu.2014.02.009 .

Shea, P., & Bidjerano, T. (2016). A National Study of differences between distance and non-distance community college students in time to first associate degree attainment, transfer, and dropout. Online Learning , 20 (3), 14–15.

Sitzmann, T., Kraiger, K., Stewart, D., & Wisher, R. (2006). The comparative effectiveness of web-based and classroom instruction: A meta-analysis. Personnel Psychology , 59 (3), 623–664.

Smith, L. A. (2007). Chaos: a very short introduction . Oxford: Oxford University Press.

Star, S. L., & Griesemer, J. R. (1989). Institutional ecology, translations and boundary objects: Amatuers and professionals in Berkely’s Museum of Vertebrate Zoology, 1907-39. Social Studies of Science , 19 (3), 387–420.

Stark, P. & Freishtat, R. (2014). An evaluation of course evaluations. ScienceOpen. Retrieved from https://www.stat.berkeley.edu/~stark/Preprints/evaluations14.pdf .

Tynan, B., Ryan, Y., & Lamont-Mills, A. (2015). Examining workload models in online and blended teaching. British Journal of Educational Technology , 46 (1), 5–15.

Uttl, B., White, C. A., & Gonzalez, D. W. (2016). Meta-analysis of faculty’s teaching effectiveness: Student evaluation of teaching ratings and student learning are not related. Studies in Educational Evaluation , 54 , 22–42.

Williams, J. (2016). College and the new class divide. Inside Higher Ed July 11, 2016.

Wladis, C., Hachey, A. C., & Conway, K. (2015). Which STEM majors enroll in online courses, and why should we care? The impact of ethnicity, gender, and non-traditional student characteristics. Computers and Education , 87 , 285–308 https://doi.org/10.1016/j.compedu.2015.06.010 .

Zhao, Y., Lei, J., Yan, B., Lai, C., & Tan, H. S. (2005). What makes the difference? A practical analysis of research on the effectiveness of distance education. Teachers College Record , 107 (8), 1836–1884. https://doi.org/10.1111/j.1467-9620.2005.00544.x .

Download references

Acknowledgements

The authors acknowledge the contributions of several investigators and course developers from the Center for Distributed Learning at the University of Central Florida, the McKay School of Education at Brigham Young University, and Scholars at Umea University, Sweden. These professionals contributed theoretical and practical ideas to this research project and carefully reviewed earlier versions of this manuscript. The Authors gratefully acknowledge their support and assistance.

Author information

Authors and affiliations.

University of Central Florida, Orlando, Florida, USA

Charles Dziuban, Patsy D. Moskal & Nicole Sicilia

Brigham Young University, Provo, Utah, USA

Charles R. Graham

Campus Skellefteå, Skellefteå, Sweden

Anders Norberg

You can also search for this author in PubMed   Google Scholar

Contributions

The Authors of this article are listed in alphabetical order indicating equal contribution to this article. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Patsy D. Moskal .

Ethics declarations

Competing interests.

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Student Perception of Instruction

Instructions: Please answer each question based on your current class experience. You can provide additional information where indicated.

All responses are anonymous. Responses to these questions are important to help improve the course and how it is taught. Results may be used in personnel decisions. The results will be shared with the instructor after the semester is over.

Please rate the instructor’s effectiveness in the following areas:

Organizing the course:

Excellent b) Very Good c) Good d) Fair e) Poor

Explaining course requirements, grading criteria, and expectations:

Communicating ideas and/or information:

Showing respect and concern for students:

Stimulating interest in the course:

Creating an environment that helps students learn:

Giving useful feedback on course performance:

Helping students achieve course objectives:

Overall, the effectiveness of the instructor in this course was:

What did you like best about the course and/or how the instructor taught it?

What suggestions do you have for improving the course and/or how the instructor taught it?

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Dziuban, C., Graham, C.R., Moskal, P.D. et al. Blended learning: the new normal and emerging technologies. Int J Educ Technol High Educ 15 , 3 (2018). https://doi.org/10.1186/s41239-017-0087-5

Download citation

Received : 09 October 2017

Accepted : 20 December 2017

Published : 15 February 2018

DOI : https://doi.org/10.1186/s41239-017-0087-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Blended learning
• Higher education
• Student success
• Student perception of instruction

For the best Oliver Wyman website experience, please upgrade your browser to IE9 or later

• Global (English)
• India (English)
• Middle East (English)
• South Africa (English)
• Brazil (Português)
• China (中文版)
• Japan (日本語)
• Southeast Asia (English)
• Belgium (English)
• France (Français)
• Germany (Deutsch)
• Italy (Italiano)
• Netherlands (English)
• Nordics (English)
• Portugal (Português)
• Spain (Español)
• Switzerland (Deutsch)
• UK And Ireland (English)

Education In The New Normal

This was first published on June 3, 2020

Covid-19 has created numerous and significant challenges to the education system, and education leadership must implement a holistic strategy to mitigate the impact of the pandemic and adapt to the new reality.

In April 2020 we published our first insights on Education Continuity During Covid-19 , which provided an overview of country responses to ensure education continuity and outlined a set of recommendations, targeted at education policymakers and delivery institutions, to build resilience into their education systems and ensure continuity during times of public crisis.

In this, the second installment, we dive deeper into the recommendations and look at core initiatives taken by education leadership in response to the pandemic and provide practical guidance and examples. 

Education Leadership Detailed Response Framework

OUR EXPERTISE  

Industries .

• Communications, Media, And Technology
• Energy And Natural Resources
• Financial Services
• Government And Public Institutions
• Health And Life Sciences
• Industrial Products
• Private Equity And Principal Investors
• Retail And Consumer Goods
• Transportation
• Velocity Podcast

capabilities 

• Climate And Sustainability
• Oliver Wyman Engineers
• People And Organizational Performance
• Performance Transformation
• Pricing, Sales, And Marketing
• Risk Management
• Turnaround And Restructuring

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Springer Nature - PMC COVID-19 Collection

The “new normal” in education

José augusto pacheco.

Research Centre on Education (CIEd), Institute of Education, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal

Effects rippling from the Covid 19 emergency include changes in the personal, social, and economic spheres. Are there continuities as well? Based on a literature review (primarily of UNESCO and OECD publications and their critics), the following question is posed: How can one resist the slide into passive technologization and seize the possibility of achieving a responsive, ethical, humane, and international-transformational approach to education? Technologization, while an ongoing and evidently ever-intensifying tendency, is not without its critics, especially those associated with the humanistic tradition in education. This is more apparent now that curriculum is being conceived as a complicated conversation. In a complex and unequal world, the well-being of students requires diverse and even conflicting visions of the world, its problems, and the forms of knowledge we study to address them.

From the past, we might find our way to a future unforeclosed by the present (Pinar 2019 , p. 12)

Texts regarding this pandemic’s consequences are appearing at an accelerating pace, with constant coverage by news outlets, as well as philosophical, historical, and sociological reflections by public intellectuals worldwide. Ripples from the current emergency have spread into the personal, social, and economic spheres. But are there continuities as well? Is the pandemic creating a “new normal” in education or simply accenting what has already become normal—an accelerating tendency toward technologization? This tendency presents an important challenge for education, requiring a critical vision of post-Covid-19 curriculum. One must pose an additional question: How can one resist the slide into passive technologization and seize the possibility of achieving a responsive, ethical, humane, and international-transformational approach to education?

The ongoing present

Unpredicted except through science fiction, movie scripts, and novels, the Covid-19 pandemic has changed everyday life, caused wide-scale illness and death, and provoked preventive measures like social distancing, confinement, and school closures. It has struck disproportionately at those who provide essential services and those unable to work remotely; in an already precarious marketplace, unemployment is having terrible consequences. The pandemic is now the chief sign of both globalization and deglobalization, as nations close borders and airports sit empty. There are no departures, no delays. Everything has changed, and no one was prepared. The pandemic has disrupted the flow of time and unraveled what was normal. It is the emergence of an event (think of Badiou 2009 ) that restarts time, creates radical ruptures and imbalances, and brings about a contingency that becomes a new necessity (Žižek 2020 ). Such events question the ongoing present.

The pandemic has reshuffled our needs, which are now based on a new order. Whether of short or medium duration, will it end in a return to the “normal” or move us into an unknown future? Žižek contends that “there is no return to normal, the new ‘normal’ will have to be constructed on the ruins of our old lives, or we will find ourselves in a new barbarism whose signs are already clearly discernible” (Žižek 2020 , p. 3).

Despite public health measures, Gil ( 2020 ) observes that the pandemic has so far generated no physical or spiritual upheaval and no universal awareness of the need to change how we live. Techno-capitalism continues to work, though perhaps not as before. Online sales increase and professionals work from home, thereby creating new digital subjectivities and economies. We will not escape the pull of self-preservation, self-regeneration, and the metamorphosis of capitalism, which will continue its permanent revolution (Wells 2020 ). In adapting subjectivities to the recent demands of digital capitalism, the pandemic can catapult us into an even more thoroughly digitalized space, a trend that artificial intelligence will accelerate. These new subjectivities will exhibit increased capacities for voluntary obedience and programmable functioning abilities, leading to a “new normal” benefiting those who are savvy in software-structured social relationships.

The Covid-19 pandemic has submerged us all in the tsunami-like economies of the Cloud. There is an intensification of the allegro rhythm of adaptation to the Internet of Things (Davies, Beauchamp, Davies, and Price 2019 ). For Latour ( 2020 ), the pandemic has become internalized as an ongoing state of emergency preparing us for the next crisis—climate change—for which we will see just how (un)prepared we are. Along with inequality, climate is one of the most pressing issues of our time (OECD 2019a , 2019b ) and therefore its representation in the curriculum is of public, not just private, interest.

Education both reflects what is now and anticipates what is next, recoding private and public responses to crises. Žižek ( 2020 , p. 117) suggests in this regard that “values and beliefs should not be simply ignored: they play an important role and should be treated as a specific mode of assemblage”. As such, education is (post)human and has its (over)determination by beliefs and values, themselves encoded in technology.

Will the pandemic detoxify our addiction to technology, or will it cement that addiction? Pinar ( 2019 , pp. 14–15) suggests that “this idea—that technological advance can overcome cultural, economic, educational crises—has faded into the background. It is our assumption. Our faith prompts the purchase of new technology and assures we can cure climate change”. While waiting for technology to rescue us, we might also remember to look at ourselves. In this way, the pandemic could be a starting point for a more sustainable environment. An intelligent response to climate change, reactivating the humanistic tradition in education, would reaffirm the right to such an education as a global common good (UNESCO 2015a , p. 10):

This approach emphasizes the inclusion of people who are often subject to discrimination – women and girls, indigenous people, persons with disabilities, migrants, the elderly and people living in countries affected by conflict. It requires an open and flexible approach to learning that is both lifelong and life-wide: an approach that provides the opportunity for all to realize their potential for a sustainable future and a life of dignity”.

Pinar ( 2004 , 2009 , 2019 ) concevies of curriculum as a complicated conversation. Central to that complicated conversation is climate change, which drives the need for education for sustainable development and the grooming of new global citizens with sustainable lifestyles and exemplary environmental custodianship (Marope 2017 ).

The new normal

The pandemic ushers in a “new” normal, in which digitization enforces ways of working and learning. It forces education further into technologization, a development already well underway, fueled by commercialism and the reigning market ideology. Daniel ( 2020 , p. 1) notes that “many institutions had plans to make greater use of technology in teaching, but the outbreak of Covid-19 has meant that changes intended to occur over months or years had to be implemented in a few days”.

Is this “new normal” really new or is it a reiteration of the old?

Digital technologies are the visible face of the immediate changes taking place in society—the commercial society—and schools. The immediate solution to the closure of schools is distance learning, with platforms proliferating and knowledge demoted to information to be exchanged (Koopman 2019 ), like a product, a phenomenon predicted decades ago by Lyotard ( 1984 , pp. 4-5):

Knowledge is and will be produced in order to be sold, it is and will be consumed in order to be valued in a new production: in both cases, the goal is exchange. Knowledge ceases to be an end in itself, it loses its use-value.

Digital technologies and economic rationality based on performance are significant determinants of the commercialization of learning. Moving from physical face-to-face presence to virtual contact (synchronous and asynchronous), the learning space becomes disembodied, virtual not actual, impacting both student learning and the organization of schools, which are no longer buildings but websites. Such change is not only coterminous with the pandemic, as the Education 2030 Agenda (UNESCO 2015b ) testified; preceding that was the Delors Report (Delors 1996 ), which recoded education as lifelong learning that included learning to know, learning to do, learning to be, and learning to live together.

Transnational organizations have specified competences for the 21st century and, in the process, have defined disciplinary and interdisciplinary knowledge that encourages global citizenship, through “the supra curriculum at the global, regional, or international comparative level” (Marope 2017 , p. 10). According to UNESCO ( 2017 ):

While the world may be increasingly interconnected, human rights violations, inequality and poverty still threaten peace and sustainability. Global Citizenship Education (GCED) is UNESCO’s response to these challenges. It works by empowering learners of all ages to understand that these are global, not local issues and to become active promoters of more peaceful, tolerant, inclusive, secure and sustainable societies.

These transnational initiatives have not only acknowledged traditional school subjects but have also shifted the curriculum toward timely topics dedicated to understanding the emergencies of the day (Spiller 2017 ). However, for the OECD ( 2019a ), the “new normal” accentuates two ideas: competence-based education, which includes the knowledges identified in the Delors Report , and a new learning framework structured by digital technologies. The Covid-19 pandemic does not change this logic. Indeed, the interdisciplinary skills framework, content and standardized testing associated with the Programme for International Student Assessment of the OECD has become the most powerful tool for prescribing the curriculum. Educationally, “the universal homogenous ‘state’ exists already. Globalization of standardized testing—the most prominent instance of threatening to restructure schools into technological sites of political socialization, conditioning children for compliance to a universal homogeneous state of mind” (Pinar 2019 , p. 2).

In addition to cognitive and practical skills, this “homogenous state of mind” rests on so-called social and emotional skills in the service of learning to live together, affirming global citizenship, and presumably returning agency to students and teachers (OECD 2019a ). According to Marope ( 2017 , p. 22), “this calls for higher flexibility in curriculum development, and for the need to leave space for curricula interpretation, contextualization, and creativity at the micro level of teachers and classrooms”. Heterogeneity is thus enlisted in the service of both economic homogeneity and disciplinary knowledge. Disciplinary knowledge is presented as universal and endowed with social, moral, and cognitive authority. Operational and effective knowledge becomes central, due to the influence of financial lobbies, thereby ensuring that the logic of the market is brought into the practices of schools. As Pestre ( 2013 , p. 21) observed, “the nature of this knowledge is new: what matters is that it makes hic et nunc the action, its effect and not its understanding”. Its functionality follows (presumably) data and evidence-based management.

A new language is thus imposed on education and the curriculum. Such enforced installation of performative language and Big Data lead to effective and profitable operations in a vast market concerned with competence in operational skills (Lyotard 1984 ). This “new normal” curriculum is said to be more horizontal and less hierarchical and radically polycentric with problem-solving produced through social networks, NGOs, transnational organizations, and think tanks (Pestre 2013 ; Williamson 2013 , 2017 ). Untouched by the pandemic, the “new (old) normal” remains based on disciplinary knowledge and enmeshed in the discourse of standards and accountability in education.

Such enforced commercialism reflects and reinforces economic globalization. Pinar ( 2011 , p. 30) worries that “the globalization of instrumental rationality in education threatens the very existence of education itself”. In his theory, commercialism and the technical instrumentality by which homogenization advances erase education as an embodied experience and the curriculum as a humanistic project. It is a time in which the humanities are devalued as well, as acknowledged by Pinar ( 2019 , p. 19): “In the United States [and in the world] not only does economics replace education—STEM replace the liberal arts as central to the curriculum—there are even politicians who attack the liberal arts as subversive and irrelevant…it can be more precisely characterized as reckless rhetoric of a know-nothing populism”. Replacing in-person dialogical encounters and the educational cultivation of the person (via Bildung and currere ), digital technologies are creating uniformity of learning spaces, in spite of their individualistic tendencies. Of course, education occurs outside schools—and on occasion in schools—but this causal displacement of the centrality of the school implies a devaluation of academic knowledge in the name of diversification of learning spaces.

In society, education, and specifically in the curriculum, the pandemic has brought nothing new but rather has accelerated already existing trends that can be summarized as technologization. Those who can work “remotely” exercise their privilege, since they can exploit an increasingly digital society. They themselves are changed in the process, as their own subjectivities are digitalized, thus predisposing them to a “curriculum of things” (a term coined by Laist ( 2016 ) to describe an object-oriented pedagogical approach), which is organized not around knowledge but information (Koopman 2019 ; Couldry and Mejias 2019 ). This (old) “new normal” was advanced by the OECD, among other international organizations, thus precipitating what some see as “a dynamic and transformative articulation of collective expectations of the purpose, quality, and relevance of education and learning to holistic, inclusive, just, peaceful, and sustainable development, and to the well-being and fulfilment of current and future generations” (Marope 2017 , p. 13). Covid-19, illiberal democracy, economic nationalism, and inaction on climate change, all upend this promise.

Understanding the psychological and cultural complexity of the curriculum is crucial. Without appreciating the infinity of responses students have to what they study, one cannot engage in the complicated conversation that is the curriculum. There must be an affirmation of “not only the individualism of a person’s experience but [of what is] underlining the significance of a person’s response to a course of study that has been designed to ignore individuality in order to buttress nation, religion, ethnicity, family, and gender” (Grumet 2017 , p. 77). Rather than promoting neuroscience as the answer to the problems of curriculum and pedagogy, it is long-past time for rethinking curriculum development and addressing the canonical curriculum question: What knowledge is of most worth from a humanistic perspective that is structured by complicated conversation (UNESCO 2015a ; Pinar 2004 , 2019 )? It promotes respect for diversity and rejection of all forms of (cultural) hegemony, stereotypes, and biases (Pacheco 2009 , 2017 ).

Revisiting the curriculum in the Covid-19 era then expresses the fallacy of the “new normal” but also represents a particular opportunity to promote a different path forward.

Looking to the post-Covid-19 curriculum

Based on the notion of curriculum as a complicated conversation, as proposed by Pinar ( 2004 ), the post-Covid-19 curriculum can seize the possibility of achieving a responsive, ethical, humane education, one which requires a humanistic and internationally aware reconceptualization of curriculum.

While beliefs and values are anchored in social and individual practices (Pinar 2019 , p. 15), education extracts them for critique and reconsideration. For example, freedom and tolerance are not neutral but normative practices, however ideology-free policymakers imagine them to be.

That same sleight-of-hand—value neutrality in the service of a certain normativity—is evident in a digital concept of society as a relationship between humans and non-humans (or posthumans), a relationship not only mediated by but encapsulated within technology: machines interfacing with other machines. This is not merely a technological change, as if it were a quarantined domain severed from society. Technologization is a totalizing digitalization of human experience that includes the structures of society. It is less social than economic, with social bonds now recoded as financial transactions sutured by software. Now that subjectivity is digitalized, the human face has become an exclusively economic one that fabricates the fantasy of rational and free agents—always self-interested—operating in supposedly free markets. Oddly enough, there is no place for a vision of humanistic and internationally aware change. The technological dimension of curriculum is assumed to be the primary area of change, which has been deeply and totally imposed by global standards. The worldwide pandemic supports arguments for imposing forms of control (Žižek 2020 ), including the geolocation of infected people and the suspension—in a state of exception—of civil liberties.

By destroying democracy, the technology of control leads to totalitarianism and barbarism, ending tolerance, difference, and diversity. Remembrance and memory are needed so that historical fascisms (Eley 2020 ) are not repeated, albeit in new disguises (Adorno 2011 ). Technologized education enhances efficiency and ensures uniformity, while presuming objectivity to the detriment of human reflection and singularity. It imposes the running data of the Curriculum of Things and eschews intellectual endeavor, critical attitude, and self-reflexivity.

For those who advocate the primacy of technology and the so-called “free market”, the pandemic represents opportunities not only for profit but also for confirmation of the pervasiveness of human error and proof of the efficiency of the non-human, i.e., the inhuman technology. What may possibly protect children from this inhumanity and their commodification, as human capital, is a humane or humanistic education that contradicts their commodification.

The decontextualized technical vocabulary in use in a market society produces an undifferentiated image in which people are blinded to nuance, distinction, and subtlety. For Pestre, concepts associated with efficiency convey the primacy of economic activity to the exclusion, for instance, of ethics, since those concepts devalue historic (if unrealized) commitments to equality and fraternity by instead emphasizing economic freedom and the autonomy of self-interested individuals. Constructing education as solely economic and technological constitutes a movement toward total efficiency through the installation of uniformity of behavior, devaluing diversity and human creativity.

Erased from the screen is any image of public education as a space of freedom, or as Macdonald ( 1995 , p. 38) holds, any image or concept of “the dignity and integrity of each human”. Instead, what we face is the post-human and the undisputed reign of instrumental reality, where the ends justify the means and human realization is reduced to the consumption of goods and experiences. As Pinar ( 2019 , p. 7) observes: “In the private sphere…. freedom is recast as a choice of consumer goods; in the public sphere, it converts to control and the demand that freedom flourish, so that whatever is profitable can be pursued”. Such “negative” freedom—freedom from constraint—ignores “positive” freedom, which requires us to contemplate—in ethical and spiritual terms—what that freedom is for. To contemplate what freedom is for requires “critical and comprehensive knowledge” (Pestre 2013 , p. 39) not only instrumental and technical knowledge. The humanities and the arts would reoccupy the center of such a curriculum and not be related to its margins (Westbury 2008 ), acknowledging that what is studied within schools is a complicated conversation among those present—including oneself, one’s ancestors, and those yet to be born (Pinar 2004 ).

In an era of unconstrained technologization, the challenge facing the curriculum is coding and STEM (science, technology, engineering, and mathematics), with technology dislodging those subjects related to the human. This is not a classical curriculum (although it could be) but one focused on the emergencies of the moment–namely, climate change, the pandemic, mass migration, right-wing populism, and economic inequality. These timely topics, which in secondary school could be taught as short courses and at the elementary level as thematic units, would be informed by the traditional school subjects (yes, including STEM). Such a reorganization of the curriculum would allow students to see how academic knowledge enables them to understand what is happening to them and their parents in their own regions and globally. Such a cosmopolitan curriculum would prepare children to become citizens not only of their own nations but of the world. This citizenship would simultaneously be subjective and social, singular and universal (Marope 2020 ). Pinar ( 2019 , p. 5) reminds us that “the division between private and public was first blurred then erased by technology”:

No longer public, let alone sacred, morality becomes a matter of privately held values, sometimes monetized as commodities, statements of personal preference, often ornamental, sometimes self-servingly instrumental. Whatever their function, values were to be confined to the private sphere. The public sphere was no longer the civic square but rather, the marketplace, the site where one purchased whatever one valued.

New technological spaces are the universal center for (in)human values. The civic square is now Amazon, Alibaba, Twitter, WeChat, and other global online corporations. The facts of our human condition—a century-old phrase uncanny in its echoes today—can be studied in schools as an interdisciplinary complicated conversation about public issues that eclipse private ones (Pinar 2019 ), including social injustice, inequality, democracy, climate change, refugees, immigrants, and minority groups. Understood as a responsive, ethical, humane and transformational international educational approach, such a post-Covid-19 curriculum could be a “force for social equity, justice, cohesion, stability, and peace” (Marope 2017 , p. 32). “Unchosen” is certainly the adjective describing our obligations now, as we are surrounded by death and dying and threatened by privation or even starvation, as economies collapse and food-supply chains are broken. The pandemic may not mean deglobalization, but it surely accentuates it, as national borders are closed, international travel is suspended, and international trade is impacted by the accompanying economic crisis. On the other hand, economic globalization could return even stronger, as could the globalization of education systems. The “new normal” in education is the technological order—a passive technologization—and its expansion continues uncontested and even accelerated by the pandemic.

Two Greek concepts, kronos and kairos , allow a discussion of contrasts between the quantitative and the qualitative in education. Echoing the ancient notion of kronos are the technologically structured curriculum values of quantity and performance, which are always assessed by a standardized accountability system enforcing an “ideology of achievement”. “While kronos refers to chronological or sequential time, kairos refers to time that might require waiting patiently for a long time or immediate and rapid action; which course of action one chooses will depend on the particular situation” (Lahtinen 2009 , p. 252).

For Macdonald ( 1995 , p. 51), “the central ideology of the schools is the ideology of achievement …[It] is a quantitative ideology, for even to attempt to assess quality must be quantified under this ideology, and the educational process is perceived as a technically monitored quality control process”.

Self-evaluation subjectively internalizes what is useful and in conformity with the techno-economy and its so-called standards, increasingly enforcing technical (software) forms. If recoded as the Internet of Things, this remains a curriculum in allegiance with “order and control” (Doll 2013 , p. 314) School knowledge is reduced to an instrument for economic success, employing compulsory collaboration to ensure group think and conformity. Intertwined with the Internet of Things, technological subjectivity becomes embedded in software, redesigned for effectiveness, i.e., or use-value (as Lyotard predicted).

The Curriculum of Things dominates the Internet, which is simultaneously an object and a thing (see Heidegger 1967 , 1971 , 1977 ), a powerful “technological tool for the process of knowledge building” (Means 2008 , p. 137). Online learning occupies the subjective zone between the “curriculum-as-planned” and the “curriculum-as-lived” (Pinar 2019 , p. 23). The world of the curriculum-as-lived fades, as the screen shifts and children are enmeshed in an ocularcentric system of accountability and instrumentality.

In contrast to kronos , the Greek concept of kairos implies lived time or even slow time (Koepnick 2014 ), time that is “self-reflective” (Macdonald 1995 , p. 103) and autobiographical (Pinar 2009 , 2004), thus inspiring “curriculum improvisation” (Aoki 2011 , p. 375), while emphasizing “the plurality of subjectivities” (Grumet 2017 , p. 80). Kairos emphasizes singularity and acknowledges particularities; it is skeptical of similarities. For Shew ( 2013 , p. 48), “ kairos is that which opens an originary experience—of the divine, perhaps, but also of life or being. Thought as such, kairos as a formative happening—an opportune moment, crisis, circumstance, event—imposes its own sense of measure on time”. So conceived, curriculum can become a complicated conversation that occurs not in chronological time but in its own time. Such dialogue is not neutral, apolitical, or timeless. It focuses on the present and is intrinsically subjective, even in public space, as Pinar ( 2019 , p. 12) writes: “its site is subjectivity as one attunes oneself to what one is experiencing, yes to its immediacy and specificity but also to its situatedness, relatedness, including to what lies beyond it and not only spatially but temporally”.

Kairos is, then, the uniqueness of time that converts curriculum into a complicated conversation, one that includes the subjective reconstruction of learning as a consciousness of everyday life, encouraging the inner activism of quietude and disquietude. Writing about eternity, as an orientation towards the future, Pinar ( 2019 , p. 2) argues that “the second side [the first is contemplation] of such consciousness is immersion in daily life, the activism of quietude – for example, ethical engagement with others”. We add disquietude now, following the work of the Portuguese poet Fernando Pessoa. Disquietude is a moment of eternity: “Sometimes I think I’ll never leave ‘Douradores’ Street. And having written this, it seems to me eternity. Neither pleasure, nor glory, nor power. Freedom, only freedom” (Pesssoa 1991 ).

The disquietude conversation is simultaneously individual and public. It establishes an international space both deglobalized and autonomous, a source of responsive, ethical, and humane encounter. No longer entranced by the distracting dynamic stasis of image-after-image on the screen, the student can face what is his or her emplacement in the physical and natural world, as well as the technological world. The student can become present as a person, here and now, simultaneously historical and timeless.

Conclusions

Slow down and linger should be our motto now. A slogan yes, but it also represents a political, as well as a psychological resistance to the acceleration of time (Berg and Seeber 2016 )—an acceleration that the pandemic has intensified. Covid-19 has moved curriculum online, forcing children physically apart from each other and from their teachers and especially from the in-person dialogical encounters that classrooms can provide. The public space disappears into the pre-designed screen space that software allows, and the machine now becomes the material basis for a curriculum of things, not persons. Like the virus, the pandemic curriculum becomes embedded in devices that technologize our children.

Although one hundred years old, the images created in Modern Times by Charlie Chaplin return, less humorous this time than emblematic of our intensifying subjection to technological necessity. It “would seem to leave us as cogs in the machine, ourselves like moving parts, we keep functioning efficiently, increasing productivity calculating the creative destruction of what is, the human now materialized (de)vices ensnaring us in convenience, connectivity, calculation” (Pinar 2019 , p. 9). Post-human, as many would say.

Technology supports standardized testing and enforces software-designed conformity and never-ending self-evaluation, while all the time erasing lived, embodied experience and intellectual independence. Ignoring the evidence, others are sure that technology can function differently: “Given the potential of information and communication technologies, the teacher should now be a guide who enables learners, from early childhood throughout their learning trajectories, to develop and advance through the constantly expanding maze of knowledge” (UNESCO 2015a , p. 51). Would that it were so.

The canonical question—What knowledge is of most worth?—is open-ended and contentious. In a technologized world, providing for the well-being of children is not obvious, as well-being is embedded in ancient, non-neoliberal visions of the world. “Education is everybody’s business”, Pinar ( 2019 , p. 2) points out, as it fosters “responsible citizenship and solidarity in a global world” (UNESCO 2015a , p. 66), resisting inequality and the exclusion, for example, of migrant groups, refugees, and even those who live below or on the edge of poverty.

In this fast-moving digital world, education needs to be inclusive but not conformist. As the United Nations ( 2015 ) declares, education should ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. “The coming years will be a vital period to save the planet and to achieve sustainable, inclusive human development” (United Nations 2019 , p. 64). Is such sustainable, inclusive human development achievable through technologization? Can technology succeed where religion has failed?

Despite its contradictions and economic emphases, public education has one clear obligation—to create embodied encounters of learning through curriculum conceived as a complicated conversation. Such a conception acknowledges the worldliness of a cosmopolitan curriculum as it affirms the personification of the individual (Pinar 2011 ). As noted by Grumet ( 2017 , p. 89), “as a form of ethics, there is a responsibility to participate in conversation”. Certainly, it is necessary to ask over and over again the canonical curriculum question: What knowledge is of most worth?

If time, technology and teaching are moving images of eternity, curriculum and pedagogy are also, both ‘moving’ and ‘images’ but not an explicit, empirical, or exact representation of eternity…if reality is an endless series of ‘moving images’, the canonical curriculum question—What knowledge is of most worth?—cannot be settled for all time by declaring one set of subjects eternally important” (Pinar 2019 , p. 12).

In a complicated conversation, the curriculum is not a fixed image sliding into a passive technologization. As a “moving image”, the curriculum constitutes a politics of presence, an ongoing expression of subjectivity (Grumet 2017 ) that affirms the infinity of reality: “Shifting one’s attitude from ‘reducing’ complexity to ‘embracing’ what is always already present in relations and interactions may lead to thinking complexly, abiding happily with mystery” (Doll 2012 , p. 172). Describing the dialogical encounter characterizing conceived curriculum, as a complicated conversation, Pinar explains that this moment of dialogue “is not only place-sensitive (perhaps classroom centered) but also within oneself”, because “the educational significance of subject matter is that it enables the student to learn from actual embodied experience, an outcome that cannot always be engineered” (Pinar 2019 , pp. 12–13). Lived experience is not technological. So, “the curriculum of the future is not just a matter of defining content and official knowledge. It is about creating, sculpting, and finessing minds, mentalities, and identities, promoting style of thought about humans, or ‘mashing up’ and ‘making up’ the future of people” (Williamson 2013 , p. 113).

Yes, we need to linger and take time to contemplate the curriculum question. Only in this way will we share what is common and distinctive in our experience of the current pandemic by changing our time and our learning to foreclose on our future. Curriculum conceived as a complicated conversation restarts historical not screen time; it enacts the private and public as distinguishable, not fused in a computer screen. That is the “new normal”.

is full professor in the Department of Curriculum Studies and Educational Technology (Institute of Education, University of Minho, Portugal). His research focuses on curriculum theory, curriculum politics, and teacher training and evaluation. Presently, he is director of the PhD Science Education Program of the University of Minho, member of the Advisory Board of the Organization of Ibero-American Studies, director of the European Journal of Curriculum Studies, and director of the European Association on Curriculum Studies.

My thanks to William F. Pinar. Friendship is another moving image of eternity. I am grateful to the anonymous reviewer. This work is financed by national funds through the FCT - Foundation for Science and Technology, under the project PTDC / CED-EDG / 30410/2017, Centre for Research in Education, Institute of Education, University of Minho.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Adorno, T. W. (2011). Educação e emancipação [Education and emancipation]. São Paulo: Paz e Terra.
• Aoki, T. T. (2011). Sonare and videre: A story, three echoes and a lingering note. In W. F. W. Pinar & R. L. Irwin (Eds.), Curriculum in a new key. The collected works of Ted T. Aoki (pp. 368–376). New York, NY: Routledge.
• Badiou A. Theory of the subject. London: Continuum; 2009. [ Google Scholar ]
• Berg M, Seeber B. The slow professor: Challenging the culture of speed in the academy. Toronto: University of Toronto Press; 2016. [ Google Scholar ]
• Couldry N, Mejias U. The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford: Stanford University Press; 2019. [ Google Scholar ]
• Daniel SJ. Education and the Covid-19 pandemic. Prospects. 2020 doi: 10.1007/s11125-020-09464-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Davies D, Beauchamp G, Davies J, Price R. The potential of the ‘Internet of Things’ to enhance inquiry in Singapore schools. Research in Science & Technological Education. 2019 doi: 10.1080/02635143.2019.1629896. [ CrossRef ] [ Google Scholar ]
• Delors J. Learning: The treasure within. Paris: UNESCO; 1996. [ Google Scholar ]
• Doll, W. E. (2012). Thinking complexly. In D. Trueit (Ed.), Pragmatism, post-modernism, and complexity theory: The “fascinating imaginative realm” of William E. Doll, Jr. (pp. 172–187). New York, NY: Routledge.
• Doll WE. Curriculum and concepts of control. In: Pinar WF, editor. Curriculum: Toward new identities. New York, NY: Routledge; 2013. pp. 295–324. [ Google Scholar ]
• Eley G. Conclusion. In: Thomas JA, Eley G, editors. Visualizing fascism: The twentieth-century rise of the global Right. Durham, NC: Duke University Press; 2020. pp. 284–292. [ Google Scholar ]
• Gil, J. (2020). A pandemia e o capitalismo numérico [The pandemic and numerical capitalism]. Público . https://www.publico.pt/2020/04/12/sociedade/ensaio/pandemia-capitalismo-numerico-1911986 .
• Grumet, M.G. (2017). The politics of presence. In M. A. Doll (Ed.), The reconceptualization of curriculum studies. A Festschrift in honor of William F. Pinar (pp. 76–83). New York, NY: Routledge.
• Heidegger M. What is a thing? South Bend, IN: Gateway Editions; 1967. [ Google Scholar ]
• Heidegger M. Poetry, language, thought. New York, NY: Harper and Row; 1971. [ Google Scholar ]
• Heidegger M. The question concerning technology and other essays. New York, NY: Harper and Row; 1977. [ Google Scholar ]
• Koepnick L. On slowness: Toward an aesthetic of the contemporary. New York, NY: Columbia University Press; 2014. [ Google Scholar ]
• Koopman C. How we became our data: A genealogy of the informational person. Chicago, IL: University of Chicago Press; 2019. [ Google Scholar ]
• Lahtinen M. Politics and curriculum. Leiden: Brill; 2009. [ Google Scholar ]
• Laist R. A curriculum of things: Exploring an object-oriented pedagogy. The National Teaching & Learning. 2016; 25 (3):1–4. doi: 10.1002/ntlf.30062. [ CrossRef ] [ Google Scholar ]
• Latour, B. (2020). Is this a dress rehearsal? Critical Inquiry . https://critinq.wordpress.com/2020/03/26/is-this-a-dress-rehearsal
• Lyotard J. The postmodern condition: A report on knowledge. Manchester: Manchester University Press; 1984. [ Google Scholar ]
• Macdonald BJ. Theory as a prayerful act. New York, NY: Peter Lang; 1995. [ Google Scholar ]
• Marope PTM. Reconceptualizing and repositioning curriculum in the 21st century: A global paradigm shift. Geneva: UNESCO IBE; 2017. [ Google Scholar ]
• Marope PTM. Preventing violent extremism through universal values in curriculum. Prospects. 2020; 48 (1):1–5. doi: 10.1007/s11125-019-09453-1. [ CrossRef ] [ Google Scholar ]
• Means B. Technology’s role in curriculum and instruction. In: Connelly FM, editor. The Sage handbook of curriculum and instruction. Los Angeles, CA: Sage; 2008. pp. 123–144. [ Google Scholar ]
• OECD . OECD learning compass 2030. Paris: OECD; 2019. [ Google Scholar ]
• OECD . Trends shaping education 2019. Paris: OECD; 2019. [ Google Scholar ]
• Pacheco, J. A. (2009). Whole, bright, deep with understanding: Life story and politics of curriculum studies. In-between William Pinar and Ivor Goodson . Roterdam/Taipei: Sense Publishers.
• Pacheco, J. A. (2017). Pinar’s influence on the consolidation of Portuguese curriculum studies. In M. A. Doll (Ed.), The reconceptualization of curriculum studies. A Festschrift in honor of William F. Pinar (pp. 130–136). New York, NY: Routledge.
• Pestre, D. (2013). Science, technologie et société. La politique des savoirs aujourd’hui [Science, technology, and society: Politics of knowledge today]. Paris: Foundation Calouste Gulbenkian.
• Pesssoa F. The book of disquietude. Manchester: Carcanet Press; 1991. [ Google Scholar ]
• Pinar WF. What is curriculum theory? Mahwah, NJ: Lawrence Erlbaum Associates; 2004. [ Google Scholar ]
• Pinar WF. The worldliness of a cosmopolitan education: Passionate lives in public service. New York, NY: Routledge; 2009. [ Google Scholar ]
• Pinar, W. F. (2011). “A lingering note”: An introduction to the collected work of Ted T. Aoki. In W. F. Pinar & R. L. Irwin (Eds.), Curriculum in a new key. The collected works of Ted T. Aoki (pp. 1–85). New York, NY: Routledge.
• Pinar WF. Moving images of eternity: George Grant’s critique of time, teaching, and technology. Ottawa: The University of Ottawa Press; 2019. [ Google Scholar ]
• Shew M. The Kairos philosophy. The Journal of Speculative Philosophy. 2013; 27 (1):47–66. doi: 10.5325/jspecphil.27.1.0047. [ CrossRef ] [ Google Scholar ]
• Spiller, P. (2017). Could subjects soon be a thing of the past in Finland? BBC News . https://www.bbc.com/news/world-europe-39889523 .
• UNESCO (2015a). Rethinking education. Towards a global common global? Paris: UNESCO.
• UNESCO (2015b). Education 2030. Framework for action . Paris: UNESCO. https://www.sdg4education2030.org/sdg-education-2030-steering-committee-resources .
• UNESCO (2017). Global citizenship education . Paris: UNESCO. https://en.unesco.org/themes/gced .
• United Nations . The sustainable development goals. New York, NY: United Nations; 2015. [ Google Scholar ]
• United Nations . The sustainable development goals report. New York, NY: United Nations; 2019. [ Google Scholar ]
• Wells W. Permanent revolution: Reflections on capitalism. Stanford, CA: Stanford University Press; 2020. [ Google Scholar ]
• Westbury, I. (2008). Making curricula. Why do states make curricula, and how? In F. M. Connelly (Ed.), The Sage handbook of curriculum and instruction (pp. 45–65). Los Angeles, CA: Sage.
• Williamson B. The future of the curriculum. School knowledge in the digital age. Cambridge, MA: MIT Press; 2013. [ Google Scholar ]
• Williamson, B. (2017). Big data in education. The digital future of learning, policy and practice . London: Sage.
• Žižek S. PANDEMIC! Covid-19 shakes the world. New York, NY: Or Books; 2020. [ Google Scholar ]

The New Normal: Innovative Informal Digital Learning After the Pandemic

• Conference paper
• First Online: 01 January 2023
• Cite this conference paper

• John Traxler   ORCID: orcid.org/0000-0002-5284-709X 7  

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1740))

Included in the following conference series:

• International Conference on ICT Innovations

224 Accesses

The global pandemic catalysed a large-scale shift across many sectors of education towards digital learning. This was motivated by the need to preserve the ongoing delivery of education. Consequently, it was conservative rather than innovative, reinforcing existing face-to-face pedagogies rather than challenging them, and only benefitting learners actually within the sectors of education, further increasing the disadvantage of those not in the education sectors. This chapter outlines some innovative informal digital learning pedagogies that could be freely exploited to contribute to a more equitable ‘new normal’.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Mihailidis, P., Cohen, J.N.: Exploring Curation as a core competency in digital and media literacy education. J. Interact. Med. Educ. 2013 (1), 2 (2013). Part 2

Google Scholar  

Trant, J.: Studying social tagging and folksonomy: a review and framework. J. Digit. Inf. 10 (1) (2009). https://repository.arizona.edu/bitstream/handle/10150/105375/trant-studyingFolksonomy.pdf?sequence=1

Gupta, M., Li, R., Yin, Z., Han, J.: Survey on social tagging techniques. ACM SIGKDD Explor. Newsl. 12 (1), 58–72 (2010)

Article   Google Scholar  

Diigo Homepage. https://www.diigo.com/ . Accessed 20 Oct 2022

Bishop, J.L., Verleger, M.A.: The flipped classroom: a survey of the research. In: ASEE National Conference Proceedings, Atlanta, GA, vol. 30, no. 9, pp. 1–18 (2013)

Yough, M., Merzdorf, H.E., Fedesco, H.N., Cho, H.J.: Flipping the classroom in teacher education: implications for motivation and learning. J. Teach. Educ. 70 (5), 410–422 (2017)

Dyson, L.E.: Student-generated mobile learning: a shift in the educational paradigm for the 21st century. anzMLearn Trans. Mob. Learn. 1 (1), 5–19 (2012)

Robin, B.: The educational uses of digital storytelling. In: Society for Information Technology & Teacher Education International Conference, pp. 709–716. Association for the Advancement of Computing in Education (AACE) (2006)

Prins, E.: Digital storytelling in adult education and family literacy: a case study from rural Ireland. Learn. Med. Technol. 42 (3), 308–323 (2017)

Bonney, R., et al.: Citizen science: a developing tool for expanding science knowledge and scientific literacy. Bioscience 59 (11), 977–984 (2009)

Newman, G., Wiggins, A., Crall, A., Graham, E., Newman, S., Crowston, K.: The future of citizen science: emerging technologies and shifting paradigms. Front. Ecol. Environ. 10 (6), 298–304 (2012)

Kapuire, G.K., et al.: Technologies to promote the inclusion of Indigenous knowledge holders in digital cultural heritage preservation. In: International Conference on Culture & Computer Science (2016)

Maasz, D., Winschiers-Theophilus, H., Stanley, C., Rodil, K., Mbinge, U.: A digital indigenous knowledge preservation framework: the 7C model—Repositioning IK holders in the digitization of IK. In: Jat, D.S., Sieck, J., Muyingi, H.-N., Winschiers-Theophilus, H., Peters, A., Nggada, S. (eds.) Digitisation of Culture: Namibian and International Perspectives, pp. 29–47. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-7697-8_3

Chapter   Google Scholar  

Ostashewski, N., Reid, D.: A history and frameworks of digital badges in education. In: Reiners, T., Wood, L.C. (eds.) Gamification in Education and Business, pp. 187–200. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-10208-5_10

Lameras, P., Arnab, S., Dunwell, I., Stewart, C., Clarke, S., Petridis, P.: Essential features of serious games design in higher education: linking learning attributes to game mechanics. Br. J. Educ. Technol. 48 (4), 972–994 (2017)

Chorney, A.I.: Taking the game out of gamification. Dalhousie J. Interdisc. Manag. 8 (1) (2012).  https://dalspace.library.dal.ca/handle/10222/16030?show=full

Kusuma, G.P., Wigati, E.K., Utomo, Y., Suryapranata, L.K.P.: Analysis of gamification models in education using MDA framework. Proc. Comput. Sci. 135 , 385–392 (2018)

Kim, B.: Game mechanics, dynamics, and aesthetics. Libr. Technol. Rep. 51 (2), 17–19 (2015)

Callaghan, M.J., McShane, N., Eguiluz, A.G., Teilles, T., Raspail, P.: Practical application of the Learning Mechanics-Game Mechanics (LM-GM) framework for Serious Games analysis in engineering education. In: 13th International Conference on Remote Engineering and Virtual Instrumentation, pp. 391–395. IEEE (2016)

Salen, T.: Weblogs and blogging constructivist pedagogy and active learning in higher education. Master’s thesis. The University of Bergen (2007)

O’Donnell, M.: Blogging as pedagogic practice: artefact and ecology. Asia Pac. Med. Educ. 17 , 5–19 (2006)

Kokotsaki, D., Menzies, V., Wiggins, A.: Project-based learning: a review of the literature. Improv. Sch. 19 (3), 267–277 (2016)

Smith, M., Gurton, P.: Flipping the classroom in teacher education. In: Walker, Z., Tan, D., Koh, N.K. (eds.) Flipped Classrooms with Diverse Learners. STE, pp. 221–238. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-4171-1_13

Dabbagh, N., Kitsantas, A.: Personal Learning Environments, social media, and self-regulated learning: a natural formula for connecting formal and informal learning. Internet High. Educ. 15 (1), 3–8 (2012)

Wilson, S., Liber, O., Johnson, M., Beauvoir, P., Sharples, P., Milligan, C.: Personal Learning Environments: challenging the dominant design of educational systems. J. E-learn. Knowl. Soc. 3 (2), 27–38 (2007)

Blaschke, L.M.: Heutagogy and lifelong learning: a review of heutagogical practice and self-determined learning. Int. Rev. Res. Open Distrib. Learn. 13 (1), 56–71 (2012)

McLoughlin, C., Lee, M.J.: Personalised and self-regulated learning in the Web 2.0 era: international exemplars of innovative pedagogy using social software. Australas. J. Educ. Technol. 26 (1), 28–43 (2010)

Moore, R.L.: Developing lifelong learning with heutagogy: contexts, critiques, and challenges. Distance Educ. 41 (3), 381–401 (2020)

Blaschke, L.M., Hase, S.: Heutagogy, technology, and lifelong learning for professional and part-time learners. In: Dailey-Hebert, A., Dennis, K.S. (eds.) Transformative Perspectives and Processes in Higher Education. ABET, vol. 6, pp. 75–94. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-09247-8_5

Eberle, J.H.: Lifelong learning. In: Self-determined Learning: Heutagogy in Action, pp. 145–157 (2013)

Traxler, J.: Learning in a mobile age. Int. J. Mob. Blended Learn. 1 (1), 1–12 (2008)

MathSciNet   Google Scholar  

Kukulska-Hulme, A., Traxler, J.: Mobile Learning: A Handbook for Educators and Trainers (Lockwood, F. (Series ed.)). Routledge, London (2005)

Traxler, J.: Learning with mobiles in the digital age. Pedagogika Spec. Monothematic Issue: Educ. Futures Digit. Age: Theory Pract. 68 (3), 293–310 (2018)

Butcher, N.: A Basic Guide to Open Educational Resources (OER). Commonwealth of Learning, Vancouver (2015)

Atkins, D.E., Brown, J.S., Hammond, A.L.: A review of the open educational resources (OER) movement: achievements, challenges, and new opportunities, vol. 164. Creative Common, Mountain View (2007)

Salmon, G.: E-Moderating: The Key to Teaching and Learning Online. Psychology Press, London (2003)

Brett, P.: Students’ experiences and engagement with SMS for learning in higher education. Innov. Educ. Teach. Int. 48 (2), 137–147 (2011)

Article   MathSciNet   Google Scholar  

Xerri, D., Campbell, C.: E-portfolios in teacher development: the better option? ELT J. 70 (4), 392–400 (2016)

Wuetherick, B., Dickinson, J.: Why ePortfolios? Student perceptions of ePortfolio use in continuing education learning environments. Int. J. ePortfolio 5 (1), 39–53 (2015)

Heinrich, E., Bhattacharya, M., Rayudu, R.: Preparation for lifelong learning using ePortfolios. Eur. J. Eng. Educ. 32 (6), 653–663 (2007)

Buchem, I., Hamelmann, H.: Microlearning: a strategy for ongoing professional development. eLearning Papers 21 (7), 1–15 (2010)

Traxler, J., Scott, H., Smith, M., Hayes, S.: Learning through the crisis helping decision-makers around the world use digital technology to combat the educational challenges produced by the current COVID-19 pandemic (No. 1). EdTech Hub (2020)

Download references

Author information

Authors and affiliations.

UNESCO Chair, Llanon, UK

John Traxler

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to John Traxler .

Editor information

Editors and affiliations.

Saints Cyril and Methodius University of Skopje, Skopje, North Macedonia

Katerina Zdravkova

Lasko Basnarkov

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Cite this paper.

Traxler, J. (2022). The New Normal: Innovative Informal Digital Learning After the Pandemic. In: Zdravkova, K., Basnarkov, L. (eds) ICT Innovations 2022. Reshaping the Future Towards a New Normal. ICT Innovations 2022. Communications in Computer and Information Science, vol 1740. Springer, Cham. https://doi.org/10.1007/978-3-031-22792-9_1

Download citation

DOI : https://doi.org/10.1007/978-3-031-22792-9_1

Published : 01 January 2023

Publisher Name : Springer, Cham

Print ISBN : 978-3-031-22791-2

Online ISBN : 978-3-031-22792-9

eBook Packages : Computer Science Computer Science (R0)

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Share full article

Advertisement

Supported by

New Nutrition Guidelines Put Less Sugar and Salt on the Menu for School Meals

The Agriculture Department finalized a new rule to bring the meals more in line with federal dietary standards.

By Linda Qiu

Reporting from Washington

School meals will soon contain less salt and sugar, but can still include chocolate milk, under new nutrition guidelines released by the Biden administration.

The Agriculture Department announced on Wednesday that it had finalized the regulation it had first proposed in February 2023 , having weakened several provisions after feedback from food companies, school nutrition professionals and over 136,000 public comments.

“All of this is designed to ensure that students have quality meals and that we meet parents’ expectation that their children are receiving healthy and nutritious meals at school,” Tom Vilsack, the agriculture secretary, said in a call with reporters on Tuesday.

The new guidelines seek to better align school meals with federal dietary standards and build on a 2010 law that aimed to make cafeteria breakfasts and lunches healthier. That law, championed by Michelle Obama when she was the first lady, became embroiled in political debate almost immediately. The Trump administration tried repeatedly to roll back nutrition standards , and the Biden administration relaxed certain provisions to provide more flexibility during the coronavirus pandemic.

About 28.6 million students received or purchased lunch through the national school lunch program in the 2023 fiscal year, and the school lunch and breakfast programs cost the federal government about $21 billion .

When the Agriculture Department proposed updates to the standards last year, school nutrition professionals called the guidelines unrealistic to enforce, and dairy groups expressed concerns over what they called a push to limit milk. The final rule reflects some of those concerns.

Under the rule, which will go into effect July 1, schools will need to limit the amount of added sugars in cereals and yogurts they serve beginning in the 2025-26 academic year and gradually step up reductions in other foods.

Added sugars currently provide about 17 percent of calories in school breakfasts and 11 percent in school lunches on average, according to a May 2022 government report . Federal dietary guidelines recommend that no more than 10 percent of daily calories come from added sugars.

Jamie B. Bussel of the Robert Wood Johnson Foundation, a health-focused nonprofit group, said the new limit represented a “significant step toward reducing kids’ risk of chronic illnesses like Type 2 diabetes and heart disease.”

The Sugar Association, a trade group, said it supported limiting added sugars in a weekly menu but called applying limits to individual products like flavored dairy products “arbitrary.” The group also warned that the new standards might lead to increased use of artificial sweeteners, which is not addressed but could have its own health ramifications .

Schools will need to reduce sodium in lunches by 15 percent from current levels and in breakfasts by 10 percent by the 2027-28 academic year. This was scaled back from a proposed reduction of 30 percent by the 2029-30 school year. Mr. Vilsack said the Agriculture Department was unable to more meaningfully cut salt because it was essentially handcuffed by a policy rider in a spending package Congress approved in March limiting sodium reduction in school meals.

Current standards limit sodium for students in grades K-5 to 1,650 milligrams for breakfast and lunch combined, and the policy rider essentially capped the level at 1,420 milligrams. Federal dietary guidelines recommend no more than 1,500 milligrams of sodium daily for children ages 4 through 8.

Dairy, too, was spared from further reductions. Students can still glug chocolate, strawberry and other flavored milks under the final rule, provided that the beverages meet the limit on added sugars.

Flavored milk was the main source of added sugars in school meals, according to the 2022 government report. The Agriculture Department had considered banning the beverages for grades K-5 under the proposed regulation. But it decided against doing so, Mr. Vilsack said, because the dairy industry “stepped up to the challenge” and is working on making flavored milk products with less sugar.

The final rule also retains the current standard requiring that 80 percent of cereals and legumes offered be whole grains. The department had considered requiring all grains to be whole, with one exception a week for a refined grain product.

The School Nutrition Association, which represents cafeteria workers and directors across the country, expressed appreciation that the finalized rule reflected its feedback. But the announcement was met with mixed reaction from the food industry and health advocates.

The International Dairy Foods Association praised the decision to preserve flavored milk but said the Agriculture Department had “missed an opportunity” to restore whole and 2 percent milk to school meals.

Nancy Brown, the chief executive of the American Heart Association, said her group was pleased by the caps on added sugars but disappointed that the rule did not require 100 percent whole grains and more significant sodium reductions.

Linda Qiu is a reporter who specializes in fact-checking statements made by politicians and public figures. She has been reporting and fact-checking public figures for nearly a decade. More about Linda Qiu