thesis about blended learning

• 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

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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.

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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.

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

CURRICULUM, INSTRUCTION, AND PEDAGOGY article

Students' perceptions of a blended learning environment to promote critical thinking.

• School of Foreign Languages, Northeast Normal University, Changchun, China

Critical thinking is considered as one of the indispensable skills that must be possessed by the citizens of modern society, and its cultivation with blended learning has drawn much attention from researchers and practitioners. This study proposed the construction of a blended learning environment, where the pedagogical, social, and technical design was directed to fostering critical thinking. The purpose of the study was to find out students' perceptions of the learning environment concerning its design and its influence on their critical thinking. Adopting the mixed method, the study used questionnaire and interview as the instruments for data collection. The analysis of the data revealed that the students generally held positive perceptions of the environment, and they believed that the blended learning environment could help promote their critical thinking in different aspects.

Introduction

The development of critical thinking has drawn attention of the education ministries and institutions of different levels in countries all over the world. In the last two decades, researchers and practitioners have been exploring the ways to integrate critical thinking cultivation into the instruction of different disciplines, proposing strategies and interventions to promote critical thinking, among which blended learning has been widely recognized (e.g., Van Gelder and Bulker, 2000 ; Gilbert and Dabbagh, 2005 ; Yukawa, 2006 ). Blended learning is proposed as focusing on optimizing achievement of learning objectives by applying the “right” personal learning technologies to the “right” person at the “right” time and “right” place ( Singh, 2003 ). A blended learning environment, integrating the advantages of the e-learning method and traditional method, is believed to be more effective than a face-to-face or online learning environment alone ( Kim and Bonk, 2006 ; Watson, 2008 ; Yen and Lee, 2011 ). Studies have been conducted to construct blended learning environments to improve students' critical thinking. Most of them, however, adopted standardized tests or coding schemes to examine the effectiveness of the learning environments on students' critical thinking ( Chou et al., 2018 ), paying less attention to students' perceptions and attitudes. Therefore, the purpose of the current study is to address this gap.

Critical Thinking

There are a vast number of definitions of critical thinking in the literature (e.g., Paul, 1992 ; Ennis, 1996 ; Fisher and Scriven, 1997 ). Despite the emphasis on different aspects, the core of critical thinking entails taking charge of one's thinking to improve it. Paul and Elder's definition and model of critical thinking were adopted in the study. According to Elder and Paul (1994) , critical thinking refers to “the ability of individuals to take charge of their own thinking and develop appropriate criteria and standards for analyzing their own thinking” (p. 34). They proposed that critical thinking is composed of three dimensions: elements of thinking, intellectual standards, and intellectual traits. People demonstrate critical thinking when they use intellectual standards (clarity, precision, accuracy, importance, relevance, sufficiency, logic, fairness, breadth, depth) to measure elements of thinking (purposes, assumptions, questions, points of view, information, implications, concepts, inferences) ( Paul and Elder, 1999 ).

Critical Thinking Cultivation With Information Communication Technology Tools

Studies applying ICT tools to cultivate critical thinking have been increasingly emerging in the literature. The systematic review conducted by Chou et al. (2018) analyzed and reported the trends and features of critical thinking studies with ICT tools. According to the findings of the review, the most often used tools include online discussion (e.g., Cheong and Cheung, 2008 ), coding or game design or Wikibooks creation (e.g., Yang and Chang, 2013 ), and concept or argument maps (e.g., Rosen and Tager, 2014 ). As for the method involved, the studies adopted both quantitative and qualitative research methods (e.g., Shamir et al., 2008 ; Yang, 2008 ; Yang and Chou, 2008 ; Butchart et al., 2009 ; de Leng et al., 2009 ; Yeh, 2009 ). Data from various measurements revealed overall positive results of using ICT tools in critical thinking cultivation (e.g., Yang, 2008 ; Allaire, 2015 ; Shin et al., 2015 ; Huang et al., 2017 ). The findings of the systematic review showed that the critical thinking-embedded activities using ICT tools were more effective than face-to-face activities in developing students' critical thinking ( Guiller et al., 2008 ; Adam and Manson, 2014 ; Eftekhari et al., 2016 ). However, students' prescriptions of the learning design or critical thinking development have not been fully addressed in the literature.

Blended Learning Environment

The concept of blended learning has been defined by several researchers and scholars. For instance, Singh and Reed (2001) defined blended learning as a learning program where more than one delivery mode is being used to optimize the learning outcome and cost of program delivery. According to Thorne (2003) , blended learning is a way of “meeting the challenges of tailoring learning and development to the needs of individuals by integrating the innovative and technological advances offered by online learning with the interaction and participation offered in the best of traditional learning” (p. 2). The above definitions indicate that blended learning can combine the advantages of both traditional face-to-face learning and e-learning and avoid the drawbacks of the two learning modes. The effectiveness of blended learning has been demonstrated by many studies, for example, the findings of a meta-analysis have shown that blended learning brings more positive impact on students learning than online and face-to-face learning ( BatdÄ, 2014 ). Despite the merits of blended learning itself, the effectiveness is determined by the proper design. How to achieve the equilibrium between e-learning and face-to-face modes is crucial to the success of the blended learning environment ( Osguthorpe and Graham, 2003 ).

This study applied the PST model developed by Wang (2008) as the framework for the environment design. As Kirschner et al. (2004) pointed out, an educational system is a unique combination of pedagogical, social, and technological components. PST model thus consists of three key components: pedagogy, social interaction, and technology. According to Wang (2008) , the pedagogical design involves the selection of appropriate content, activities, and the way to use the resources; the social design refers to the construction of a safe and comfortable environment where learners can share and communicate; the technical design provides learners with a technical space of availability, easy access and attractiveness. In any learning environment, the three components play different roles. The technical design offers a basic condition for pedagogical and social design, while the pedagogical and social design is considered as the most important factor that influences the effectiveness of learning ( Wang, 2008 ).

Perceptions of Blended Learning Environment

It has been acknowledged that students' perceptions and satisfaction are important for determining the quality of blended learning environment ( Naaj et al., 2012 ). Studies have been conducted to examine students' views regarding a blended learning environment and factors influencing it. For example, Bendania (2011) study found that students hold positive attitudes toward the blended learning environment and the influencing factors mainly include experience, confidence, enjoyment, usefulness, intention to use, motivation, and whether students had ICT skills. The positive view was also reported in the study done by Akkoyunlu and Yilmaz (2006) , and it was found to be closely related to students' participation in the online discussion forum. Findings from other studies (e.g., Dziuban et al., 2006 ; Owston et al., 2006 ) also revealed students' positive attitudes toward the blended learning environment, and the satisfaction could be attributed to features like flexibility, convenience, reduced travel time, and face-to-face interaction. Some studies, however, reported some negative perceptions of the blended learning environment. For example, the results of the study of Smyth et al. (2012) showed that the delayed feedback from the teacher and poor connectivity of the internet were perceived as major drawbacks of the environment. In another study conducted by Stracke (2007) , lack of reciprocity between traditional and online modes, no use of printed books for reading and writing, and use of the computer as a medium of instruction was considered as major reasons for students withdraw from the blended course. These findings indicate that students' negative attitudes toward the blended learning environment mainly come from the inadequate design ( Sagarra and Zapata, 2008 ).

The review of the above studies indicates that applying ICT tools to cultivate critical thinking has gained much popularity and produced positive results. Few studies, however, focus on students' perceptions of a learning environment designed to promote critical thinking despite the fact that many studies have been conducted to explore students' perceptions of a blended learning environment in general. Therefore, the purpose of the current research is to investigate students' perceptions of a blended learning environment with the orientation of critical thinking development.

Research Design

Research questions.

By adopting the mixed method, this study aims to answer the following two questions:

1. What are students' perceptions of the blended learning environment to promote critical thinking?

2. How do students perceive the impact of the blended learning environment on the development of their critical thinking?

Context and Participants

The study was carried out in the course of Practical English Writing which is a branch of the comprehensive English course for first-year non-English majors at a Normal University in mainland China. The 6-week course adopted a mixed learning mode of classroom face-to-face and online learning. The face-to-face class ran once a week and each class was 90 min. The e-learning tasks were assigned either before or after the class. Six independent learning centers with networked computers were available for students to use and the whole campus was covered with Wi-Fi signal.

The participants of the study involved a total of 90 non-English major students (33 males and 57 females) aging from 18 to 20 in 2020. The students were allocated into classes of Level A after the placement test of English proficiency, which means their English was about higher intermediate level. Adopting the International Critical Thinking Reading and Writing Test ( Paul and Elder, 2006 ), which was developed from Paul and Elders' thinking model, the study assessed students' critical thinking level at the beginning of the course and found that the students' overall critical thinking level was at the lower medium level. But their information literacy level was sufficient to cope with the online platform and the software in the blended learning environment. Before the implementation of the course, the instructor informed the students about the study, and the consent forms were signed by the students.

Environment Design

For the learning environment to achieve the purpose of developing learners' critical thinking, its structural components should be designed to provide favorable conditions for critical thinking cultivation. A systematic review conducted by Lu (2018) has identified a series of favoring conditions that could promote the students' critical thinking, which include (a) critical thinking as one of the teaching objectives, (b) tasks involving the operation of ideas, (c) authentic context, (d) rich and diversified resources, (e) interaction and collaboration, (f) scaffolding and guidance, (g) communicative tools. These conditions were mapped to the design of the components of the PST learning environment model and the designing strategies were generalized from the instruction practice to guide the detailed design of the environmental components.

Pedagogical Design

In terms of the pedagogical design, the thinking skills that can be cultivated were first decided according to the particular learning content. Aiming at promoting the thinking skills, the learning tasks which mostly introduced problems in the “real” context and involve the operation of ideas were designed. Furthermore, rich and diversified resources were provided to the students. The specific strategies of pedagogical design are listed in Table 1 .

Table 1 . Strategies for pedagogical design.

When designing the learning objectives of the activities, the basic concepts and frameworks of critical thinking were introduced to the students, making them aware of its meaning and significace. Furthermore, students were informed of the thinking skills targeted and their importance. When students associated the thinking skills with the tasks, they would try to use the skills to accomplish them.

In order to enable tasks to involve more operations of ideas, writing, discussion, and evaluation activities were given the priority to provide more opportunities for students to communicate with each other and reflect upon their ideas. Besides, the topics of these activities were chosen to induce more collision of ideas. For example, in learning to write complaint letters, students were assigned the roles of customers who made the complaints and the managers who responded to the complaints. In such an activity, students could realize the existence of different perspectives and think more adequately and deeply.

The creation of a relatively real context drew on the following two strategies: One is to provide sufficient details. In the case of the job application writing, details such as the information about the potential employer were provided to the students so that they could consider themselves as “real” potential employees. The other strategy is to create interesting situations. The contexts described were usually attractive to the students, which helped arouse students' interest in completing the tasks.

With the purpose of collecting sufficient and diversified resources, both traditional and online media were included. Since the materials in the textbook are rather limited, the relevant online resources would make complementation for students to have sufficient resources to deal with. To meet the multi-angle nature of resources, the information collected came from different positions and perspectives. For instance, the students were introduced to the websites both for job hunting and recruitment so that they could read information from the perspectives of both employers and potential employees. To help students conduct resource searches by themselves, online resources such as the Online Writing Lab of Purdue University were presented to them to conduct searches. The search was usually directed by a clear question or a problem, and students needed to accurately identify the target source. Some search engines were also introduced to the students, enabling them to compare and select the relevant resources. Students needed to first define what their search objectives were, then assess the search and query results one by one, and finally synthesize the resources to make a reasonable decision.

Social Design

With the purpose of cultivating students' critical thinking in the environment, interactions and collaborations of different types were stressed in the design (see Table 2 ). Furthermore, the scaffold and guidance from the teacher and the peer were designed to provide support to the students.

Table 2 . Strategies for social design.

In designing interaction and collaboration-rich community, the strategies were applied to target both student-student and student-teacher communities. In terms of student-student community, students were grouped according to their levels and the requirements of the activities. Specifically, in a demanding task, students of different academic levels were grouped to ensure the implementation. In a relatively free discussion, students were grouped according to their own will so that they could feel more comfortable sharing their ideas. Also, various types of interactions such as information exchange, discussion, debate were designed. With the change of partners, roles, and tasks, different critical thinking skills were trained. As for the student-teacher community, the student-teacher communication was facilitated through various forms of teacher-student interaction, such as teachers' feedback, office hour, and communications on Tencent QQ, which were necessary to keep students on the right track of developing thinking skills. With various opportunities of communicating with the teacher, students would not feel powerless or frustrated when facing difficult tasks, thus ensuring the achievement of the learning objectives.

Four strategies were employed when designing the scaffolding and guidance. First, the process of thinking was highlighted. When the focus fell on critical thinking processes such as establishing viewpoints, making assumptions, and evaluating information, students had examples to follow when they conducted these activities independently. Second, the role of peers was given full play. In many cases, the demonstration of peers was more direct and effective for the students to develop critical thinking skills. Third, the teacher consciously created a “democratic” classroom and online atmosphere, where students could express their opinions without fearing judgment from the “authority” or other people. Fourth, the teacher established awarding incentives to encourage students to take the initiative to meet challenges and develop thinking. For example, if one student's feedback to others' work was deeper and more thorough, the instructor gave the student more marks and demonstrated the work to the whole class with their permission.

Technological Design

Moodle (Modular Object-Oriented Dynamic Learning Environment) was the main platform of the e-learning environment. A composition reviewing and grading software TRP (Teaching Resources Platform) was also used to facilitate teachers' grading of the compositions. TRP mainly focuses on the mistakes related to language and grammar, which could help direct teachers' attention to the composition's structure, logic, coherence, and other aspects. In addition, Tencent QQ, a social networking software frequently used by students, was selected to send messages and notices to students.

As shown in Table 3 , both synchronous and asynchronous instruments were applied to provide sufficient communication among students in designing communicative tools. When designing the synchronous instruments, the instructor used the Tencent QQ, which could conveniently support the simultaneous real-time communication between learners and encourage group members to fully communicate with each other. The discussion board of Moodle was used as asynchronous tools, and sufficient time was given to the students to respond to other people's opinions or solve problems. The students could use the time to find information, consult others and translate complex ideas into words.

Table 3 . Strategies for technological design.

Research Instruments

Learning environment questionnaire.

The questionnaire adapted from the Web-Based Learning Environment Instrument (WEBLEI) was used to elicit the information of students' perception of the learning environment. The original WEBLEI questionnaire was first created and subsequently modified by Chang and Fisher for investigating online learning environments in University settings. The primary purpose of the questionnaire was to capture “students' perception of web-based learning environments” ( Chang and Fisher, 2003 , p. 9). The questions in the WEBLEI questionnaire are able to cover the three elements of the PST learning environment model. The researcher modified the questionnaire according to the context of the current study. The Cronbach alpha coefficients indicated the acceptable reliability of the modified questionnaire (see Table 4 ).

Table 4 . Cronbach alpha coefficients for modified WEBLEI.

In order to explore students' perceived improvement of critical thinking and the in-depth reasons behind students' perceptions of the learning environment and critical thinking instruction, interviews were conducted after the administration of the adapted WEBLEI questionnaire. Eight students were randomly chosen and invited to the interview one by one. The interviews lasted about 30 min and were audio-recorded with the participants' approval.

Data Analysis

Both quantitative and qualitative data were collected for this study. In terms of quantitative analysis, descriptive statistics were used to describe the means, standard deviations. As for qualitative data, the recordings of the interviews were transcribed for content analysis. The content about the perceptions of the environment was categorized with the outline of the learning environment components. Regarding the development of students' critical thinking, the “elements of thinking” from Paul and Elder's thinking model formed the framework for data analysis. The relevant script was examined and coded according to the framework by the researcher and her collegue to generalize the aspects of critical thinking improvement.

Results and Discussion

Students' perceptions of the environment, students' perception of the pedagogical design.

The means and standard deviation scores of students' perception of the pedagogical design are listed in Table 5 . The overall mean score was 3.86 (SD = 0.79), suggesting that students were generally satisfied with the pedagogical design. Item 1 (M = 3.98, SD = 0.80) (The learning objectives are clearly stated), Item 4 ( M = 3.93, SD = 0.83) (Expectations of assignments are clearly stated), and Item 5 (M = 4, SD = 1.00) (Activities are planned carefully) got particularly high scores, which indicates that students were aware of the careful design of the activities, content, and context.

Table 5 . Students' Perceptions of the Environment.

The students' positive attitude toward the pedagogical design was also revealed from the interview, in which they expressed their satisfaction with the design of tasks and contexts. For example, Student A expressed that the course was designed in the way that they needed to “find solutions to the problems” by themselves most of the time and he also enjoyed the discussions in class. Student C recognized the relative authentic contexts of the tasks, which helped her devote herself to the tasks. She mentioned that in learning to write a CV, the teacher asked the students to imagine the situation in which they were about to graduate and hunt a job. “I felt the topic was very relevant to me, so I was motivated to do this task well.” She told the interviewer.

Apart from the positive opinions, some students expressed their concern about the pedagogical design. For example, Student H said, “The online learning added to our workload. Sometimes I was scared of all the online assignments we had to finish after class.” And student G had difficulty adapting to this learning approach. “It seemed that we were learning by ourselves. I am not sure whether I have learned enough knowledge. I would rather learn how to write from the teacher.”

Students' Perception of Social Design

As seen from Table 5 , the overall mean score of the social design was 3.90 ( M = 0.82), indicating students' generally positive attitude toward the social design. The data gathered from the students' interviews also suggested that students were satisfied with the social design. For example, student B mentioned that she always received encouragement and help when dealing with difficult tasks. Item 11 ( M = 4.07, SD = 0.65) (Other students respond promptly to my request), Item 12 ( M = 4.09, SD = 0.91) (The teachers give me quick comments on my work) and Item 14 ( M = 4.07, SD = 0.58) (I was supported by a positive attitude from my teacher and my classmates) scored higher than Item 9 ( M = 3.47, SD = 1.01) (I can ask my teacher what I do not understand) and Item 10 ( M = 3.79, SD = 0.78) (I can ask other classmates what I do not understand). This finding reveals that in the environment, both students and teachers responded to others promptly, but students had considerations when they needed to consult others.

When asked the reason for this, the students suggested that the teacher and the environment did provide them with the opportunity to seek help, but sometimes they felt reluctant to trouble others. Student E mentioned when he found something he failed to understand, he would prefer to figure it out by himself first and then seek help from the teacher and classmates. He told the interviewer: “I thought the teacher was busy, and my classmates were also busy, so I would prefer to figure it out by myself.”

Students' Perceptions of Technical Design

As for the technical design (see Table 5 ), the average score is 3.73 (SD = 0.85), which suggests that the environment provided relatively sufficient technological support to the students. Item 16 ( M = 3.93, SD = 0.92) (The online material is available at locations suitable for me) and Item 19 ( M = 4, SD = 0.97) (I decide when I want to learn) got higher scores, which indicates that students could enjoy the convenience of “anywhere” and “anytime” in the learning environment.

This positive attitude was demonstrated in the interview data collected from Student F who expressed his appreciation for the freedom and the sense of control brought by asynchronous discussion. He said, “I could finish the task at the time that is convenient for me as long as I did not miss the deadline. I like it.”

One thing worth noticing is that the mean score of Item 20 (Using blended learning allowed me to explore the interest of my own) is 3.18 (SD = 0.68), which falls toward the middle of the 1–5 scale. This score reveals that students did not think the resources of the blended learning environment play an important role in exploring their own areas of interest. In the interview, student D expressed that he did not find the resources very interesting, for the range of the topics was rather limited, and he was not attracted by the resources provided.

In sum, students' ratings on different dimensions of the questionnaire suggest that students perceived the productiveness of the learning environment in a generally positive way. This result is consistent with the studies exploring students' perceptions of the blending learning environment in general (e.g., Akkoyunlu and Yilmaz, 2006 ; Dziuban et al., 2006 ; Owston et al., 2006 ; Bendania, 2011 ; Wang and Huang, 2018 ). In the study conducted by Wang and Huang (2018) , a blended environment was also constructed from the pedagogical, social, and technical perspectives. The findings of the study reveal that students are generally positive toward the design of the learning environment. This may suggest that students would perceive the learning environment positively if the elements of the blended learning environment are carefully designed. Despite the generally positive attitudes toward the learning environment, some students expressed their concern about the workload and adaptation to the way of learning in the interview. In study Stracke (2007) , the way of learning was also found to make the students withdraw from the blended course. The findings indicate that some students may need more time to adapt to more student-centered learning.

Students' Perceived Impact of the Blended Learning Environment on the Development of Their Critical Thinking

Drawing mainly on Paul and Elder's framework of thinking elements, the following themes emerged as to the students' perceived improvement of critical thinking after data analysis and are elucidated through students' quotations.

Gaining a Deeper Understanding of the Concept of “Critical Thinking”

In the interview, students talked about their improvement in understanding the concept of critical thinking. For example, Student D expressed that the environment helped him clarify the concept of critical thinking. He used to consider the concept as closely related to “criticizing” because of its Chinese translation and came to realize that it was closer to the concept of “rational thinking.”

Some students also expressed that the course helped them realize the importance of critical thinking. As the teacher clearly informed the students of the specific critical thinking skills each task aimed to cultivate, students realized that “critical thinking is not an abstract concept, but concrete ways of guiding people to solve problems” (Student B).

Using Facts and Evidence to Support One's Own Opinion

In the interview, students also talked about the change they experienced when forming and supporting their opinion. They started to recognize the importance of facts and evidence in their writing. Student E told the interviewer that he learned that supporting ideas were very important to make one's opinion accepted. He said: “In accomplishing the writing tasks of the course, I gradually learned to provide arguments with further explanations, examples and,… maybe some data.”

Some students also suggested that facts and evidence were important for them to convince others in the discussions. Student B said: “In the past when someone disagreed with me, I usually felt sad and angry. I would either remain silent or quarrel with them. In this course, I learned that if I wanted others to accept my opinion, I needed to convince them with evidence such as facts and information.” She also felt excited that her well-presented opinions were accepted several times during the discussion with her team members.

Thinking From Multiple Perspectives

Another perceived effect is thinking from multiple perspectives, which was mentioned by many students. For example, Student A described how a particular activity helped him recognize the importance of different perspectives and how his own writing benefited from a particular activity in the course. “The teacher asked some of us to play the role of employer and I was assigned this role. When I thought from the employer's perspective, I knew what kind of employee I needed… When I wrote my job application letter, I had a very clear idea what to include in my letter.” (Student A) Student F also mentioned that recognizing different perspectives helped him finish writing the complaint letter well. According to him, he not only mentioned the dissatisfaction in the complaint letter but also stated the potential negative impact on the company to which he sent the letter.

Exploring and Clarifying the Purpose Behind the Texts or Behaviors

The interviewees also mentioned that they learned to explore and clarify the purpose behind the texts or behaviors. Some students explained how they started to consider purpose as an important component in their writing. Student H told the interviewer that when the teacher started to teach a new genre, she always asked the students to discuss under what circumstances they could meet or use this type of writing, and why they needed it in the daily life. “In this way, I understand that there should be a clear purpose behind each writing. And… and when I tried to finish my own writing task, I also put the writing purpose into my consideration.” said Student H.

Some students also told the interviewer that they gradually learned to avoid distraction and stick to the purpose when they conducted a discussion. According to student G, the students tended to talk about irrelevant things when they had discussions at the beginning of the course. With the instructors' constant reminding, they could realize whether they strayed from the point and returned to the right track in time at the end of the semester.

In summary, the data from the interview suggest that students could perceive their critical thinking development in different thinking dimensions. Furthermore, according to the students' opinion, their development in critical thinking was also manifested in their writing and even transferred to other activities. As for the promoting factors of the development, the students recognized the importance of learning environment design, especially the pedagogical design and the social design. For example, students attributed their deeper understanding of the concept to the instructor's deliberate introduction of critical thinking and focus on the development of thinking skills in the activity design. Also, they believed that the teachers' guidance and peers' scaffold enabled them to realize the importance of multiple perspectives. These factors were also found to promote students' critical thinking in the systematic review conducted by Chou et al. (2018) . This suggests that designing the elements of the learning environment to provide favorable conditions for critical thinking development could bring positive effects.

Limitations and Implications

This study proposed the construction of a blended learning environment to promote critical thinking in terms of pedagogical, social, and technical design and explored students' perceptions of the environment design and their perceived impact on the improvement of critical thinking. The results of the study suggests that students are generally satisfied with the design of the learning environment, and students considered the learning environment helpful in improving critical thinking. Even though the study made a contribution to the instructional design aiming at critical thinking promotion in a blended learning environment, some limitations should be duly noted. First, because the participants of the study were 90 students in the same University, the relative homogeneity of the context may present a possible connection with the result. Therefore, replication is recommended with larger and more diverse samples. Second, the study was not able to present the relationship between environmental design and critical thinking development quantitively. Further study could focus on the correlation between design strategies and the improvement of specific thinking skills, or the predictive capability of elements design for the promotion of critical thinking.

This study also has some implications for critical thinking cultivation in the instruction of specific disciplines. On the one hand, the cultivation of students' critical thinking requires the detailed design of the blended learning environment. Special attention needs to be paid to pedagogical, social, and technical design covering factors such as learning objectives, student interaction, and ICT tools. On the other hand, students' troubles and challenges such as the extra workload and emotional factors should be taken into consideration when designing the learning environment.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Ethics Statement

The studies involving human participants were reviewed and approved by School of Foreign Languages, Northeast Normal University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

DL designed and implemented the learning environment, collected and analyzed the data, and wrote the article.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: students' perceptions, blended learning environment, critical thinking, design, survey

Citation: Lu D (2021) Students' Perceptions of a Blended Learning Environment to Promote Critical Thinking. Front. Psychol. 12:696845. doi: 10.3389/fpsyg.2021.696845

Received: 18 April 2021; Accepted: 31 May 2021; Published: 25 June 2021.

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Copyright © 2021 Lu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Dan Lu, lud090@nenu.edu.cn

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Blended Learning Adoption and Implementation in Higher Education: A Theoretical and Systematic Review

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• Bokolo Anthony Jr.   ORCID: orcid.org/0000-0002-7276-0258 1 ,
• Adzhar Kamaludin 2 ,
• Awanis Romli 2 ,
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Technological innovations such as blended learning (BL) are rapidly changing teaching and learning in higher education, where BL integrates face to face teaching with web based learning. Thus, as polices related to BL increases, it is required to explore the theoretical foundation of BL studies and how BL were adopted and implemented in relation to students, lecturers and administration. However, only fewer studies have focused on exploring the constructs and factors related to BL adoption by considering the students, lecturers and administration concurrently. Likewise, prior research neglects to explore what practices are involved for BL implementation. Accordingly, this study systematically reviews, synthesizes, and provides meta-analysis of 94 BL research articles published from 2004 to 2020 to present the theoretical foundation of BL adoption and implementation in higher education. The main findings of this study present the constructs and factors that influence students, lecturers and administration towards adopting BL in higher education. Moreover, findings suggest that the BL practices to be implemented comprises of face-to-face, activities, information, resources, assessment, and feedback for students and technology, pedagogy, content, and knowledge for lecturers. Besides, the review reveals that the ad hoc, technology acceptance model, information system success model, the unified theory of acceptance and use of technology, and lastly diffusion of innovations theories are the mostly employed theories employed by prior studies to explore BL adoption. Findings from this study has implications for student, lecturers and administrators by providing insights into the theoretical foundation of BL adoption and implementation in higher education.

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1 Introduction

Blended learning (BL) has increasingly been utilized in higher education as it has the advantages of both traditional and online teaching approaches (Poon 2014 ). Findings from prior studies Edward et al. ( 2018 ); Ghazal et al. ( 2018 ) indicated that BL approach enhances students’ learning engagement and experience as it creates a significant influence on students’ awareness of the teaching mode and learning background. BL moves the emphasis from teaching to learning, thus enabling students to become more involved in the learning process and more enthused and, consequently, improves their perseverance and commitment (Ismail et al. 2018a ). Poon ( 2014 ) concluded that BL is likely to be developed as the leading teaching approach for the future as one of the top ten educational trends to occur in the twentyfirst century. Poon ( 2014 ) started that the question is not whether higher education should adopt BL but rather the question should be aligned to the practice that should be included for successfully BL implementation.

The phrase blended learning was previously associated with classroom training to e-learning activities (Graham et al. 2013 ). Accordingly, BL is the integration of traditional face-to face and e-learning teaching paradigm (Wong et al. 2014 ). BL employs a combination of online-mediated and face-to-face (F2F) instruction to help lecturers attain pedagogical goals in training students to produce an algorithmic and constructive rational skill, aids to enhance teaching qualities, and achieve social order (Subramaniam and Muniandy 2019 ). BL entails the combination of different methods of delivery, styles of learning, and types of teaching (Kaur 2013 ). BL is frequently used with terms such as integrated, flexible, mixed mode, multi-mode or hybrid learning (Garrison and Kanuka 2004 ; Moskal et al. 2013 ). BL comprises integration of various initiatives, achieved by combining of 30% F2F interaction with 70% IT mediated learning (Anthony et al. 2019 ). Similarly, Owston et al. ( 2019 ) recommended that a successful BL delivery comprises of 80% high quality online learning integrated with 20% classroom teaching that is linked to online content. Respectively, BL is the combination of different didactic approaches (cooperative learning, discovery learning expository, presentations, etc.) and delivery methods (personal communication, broadcasting, publishing, etc.) (Graham 2013 ; Klentien and Wannasawade 2016 ).

Research has found that online systems possess the capability of providing platforms for competent practices in offering alternative to real-life environment, offering students a usable avenue for learning which support students to improve the quality of learning (Wong et al. 2014 ; Ifenthaler et al. 2015 ). When prudently and accurately deployed, IT can be deployed to achieve a reliable learning experience with practical relevancy to engage and motivate students (Tulaboev 2013 ). Thus, BL facilitates students to not only articulate learning but to also test on the knowledge they have attained through the semester (Aguti et al. 2013 ). Moreover, BL offers flexibility for students and lecturer, improved personalization, improved student outcomes, encourages growth of autonomy and self-directed learning, creates prospects for professional learning, reduced cost proficiencies, increases communication between students and lecturer, and among students (So and Brush 2008 ; Spring et al 2016 ). BL emboldens the reformation of pedagogic policies with the prospective to recapture the ideals of universities (Heinze and Procter 2004 ). BL seeks to produce a harmonious and coherent equilibrium between online access to knowledge and traditional human teaching by considering students' and lecturers' attitudes (Bervell and Umar 2018 ). BL therefore remains a significant pedagogical concept as its main focus is aligned with providing the most effective teaching and learning experience (Wang et al. 2004 ).

BL offers access to online resources and information that meet the students’ level of knowledge and interest. It supports teaching conditions by offering opportunities for professional collaboration, and also improve time adeptness of lecturers (Guillén-Gámez et al. 2020 ; Owston et al. 2019 ). BL proliferates students’ interest in their individual learning progression (Chang-Tik 2018 ), facilitates students to study at their own speed, and further organize students for future by providing real-world skills (Ustunel and Tokel 2018 ), that assist students to directly apply their academic skills, self-learning abilities, and of course computer know how into the working force (Güzer and Caner 2014 ; Yeou 2016 ). As pointed out by Al-shami et al. ( 2018 ) BL improves social communication in university’ communities, improves students’ aptitude and self-reliance, increased learning quality, improve critical thinking in learning setting and incorporate technology as an operative tool to convey course contents to students (Bailey et al. 2015 ; Baragash and Al-Samarraie 2018a ).

Existing studies mainly considered BL in the context of students and lecturers in improving teaching and learning. Prior studies paid attention to BL adoption towards improving the quality of student learning and lecturers teaching. But only fewer studies explored BL implementation process as well explored administrators’ who initiate policies related to BL adoption in higher education. To fill this gap in knowledge, this current study aims to systematically reviews and synthesizes prior studies that explored BL adoption and implementation related to students, lecturers and administration based on the following six research questions:

RQ1 What are the research methods, countries, contexts, and publication year of selected BL studies?

RQ2 Which BL studies proposed model related to BL adoption in higher education?

RQ3 Based on RQ2 what are the theories, location, and context of the selected BL studies?

RQ4 Based on RQ3 what are the constructs of the identified theories employed to explore BL adoption in higher education?

RQ5 What are the constructs and factors that influence students, lecturers and administration towards adopting BL?

RQ6 What are the practices involved for BL implementation in higher education?

Therefore, to address the research questions this study review and report on BL adoption model (constructs and factors), BL implementation processes, prior theories employed, and related studies that were mainly focused on BL adoption in relation to students, lecturers, and administrator’s perspective. The remainder of the article is organized as follows. Section  2 is the literature review. Section  3 is the methodology and Sect.  4 describes the findings and discussion. Section  5 is the implications and Sect.  6 is the conclusion, limitation, and future works.

2 Literature Review

Learning in higher education refers to process of acquiring new knowledge, skills, intellectual abilities which can be utilized to successfully solve problems. The deployment of technologies in teaching and learning is not a new paradigm in higher education (Poon 2012 ). Undeniably, in the twentyfirst century students are familiar with digital environments and therefore lecturers are encouraged to use Information Technology (IT) in teaching to stimulate and employ students’ learning (Ifenthaler and Widanapathirana 2014 ; Edward et al. 2018 ). Teaching and learning with the aid of BL practices have become a common teaching approach to involve students in learning (Garrison and Kanuka 2004 ). As such, BL has progressed to incorporate diverse learning strategies and is renowned as one of the foremost trends in higher education (Ramakrisnan et al. 2012 ). BL provides pedagogical productivity, knowledge access, collective collaborations, personal development, cost efficiency, simplifies corrections and further resolves problems related to attendance (Mustapa et al. 2015 ). Findings from prior studies (Wai and Seng 2015 ; Nguyen 2017 ) suggested that BL offers benefits and is also productive than traditional e-learning.

BL in higher education is a prevailing approach to create a more collaborative and welcoming learning environment to curb students' anxiety and fear of making mistakes (Wong et al. 2014 ). Adopted in universities in the late 1990s (Edward et al. 2018 ), it found wider acceptance in the 2000s with many more university courses offered in blended mode (Graham et al. 2013 ). BL employs a combination of online-mediated and face-to-face instruction to help lecturers attain pedagogical goals in training students to produce algorithmic and constructive rational skills, aids to enhance teaching qualities and achieve social order (Kaur 2013 ). Some researchers [such as Bowyer and Chambers ( 2017 )] argued that technology integration in teaching promotes learning via discovery. And adds interactivity and more motivation, leading to better feedback, social interactions, and use of course materials (Sun and Qiu 2017 ).

As seen in Fig.  1 , BL implementation usually involves F2F and other corresponding online learning delivery methods. Normally, students attend traditional lecturer-directed F2F classes with computer mediated tools to create a BL environment in gaining experiences and also promote learners’ learning success and engagement (Moskal et al. 2013 ; Baragash and Al-Samarraie 2018b ). In fact, Graham ( 2013 ); Graham et al. ( 2013 ) projected that BL will become the new course delivery model that employs different media resources to strengthen the interaction among students. BL provide motivating and meaningful learning through different asynchronous and synchronous teaching strategies such as forums, social networking, live chats, webinars, blog, etc. that provides more opportunities for reflection and feedback from students (Graham 2013 ; Moskal et al. 2013 ; Dakduk et al. 2018 ).

Key aspects of BL derived from (Graham 2013 ; Moskal et al. 2013 )

BL is facilitated with virtual learning management systems such as Blackboard WebCT, Moodle, and other Web 2.0 platforms which are employed to facilitate collaborative learning between students and lecturers (Edward et al. 2018 ; Anthony et al. 2019 ). Accordingly, Aguti et al. ( 2014 ) stated that 80 percent of institutions in developed regions dynamically employ BL approach to support teaching and learning, with 97 percent of institutions reported to be deploying one or more forms of IT mediated learning. Figure  1 indicates that BL instructional design and type of delivery includes online activities such as wordbook, reading materials, online writing tool, message board, web links, tutorials, discussion forum, reference material, simulations, quizzes, etc. (Anthony et al. 2019 ). Conversely, F2F teaching involves lectures, laboratory activities, assessment skill practices, presentation, individual/group, and discussions carried out by the lecturer to examine the learning performance of students (Sun and Qiu 2017 ).

There has been rapid development in BL adoption focused on improving teaching and learning outcome, thus prior studies assessed the effectiveness of BL by comparing the traditional teaching and online teaching (Van Laer and Elen 2020 ). However, there are limited studies that investigated the theoretical foundation of BL adoption and implementation for teaching and learning (Wai and Seng 2015 ), and very limited studies focused on investigating administrative adoption related to BL. To this end, Garrison and Kanuka ( 2004 ) mentioned that it is important to examine BL adoption from the lens of institutions administrators. Researchers such as Wong et al. ( 2014 ) argued that while there are studies in BL, research that focused on BL adoption and implementation are limited, and that this is a gap to be addressed. Given the above insights, it is felt that more BL based research is needed to guide policy makers to strategically adopt BL in higher education towards improving learning and teaching. Therefore, this study systematically reviews and synthesizes prior studies that explored students, lecturers and administration adoption and implementation of BL.

3 Methodology

It is important to carry out an extensive literature review before starting any research investigation (Anthony et al. 2017a ). Literature review finds research gaps that exists and reveals areas where prior studies has not fully explored (Anthony et al. 2017b ). Likewise, a systematic literature review is a review that is based on unambiguous research questions, defines and explores pertinent studies, and lastly assesses the quality of the studies based on specified criteria (Al-Emran et al. 2018 ). Accordingly, this study followed the recommendation postulated by Kitchenham and Charters’s ( 2007 ) in reporting a systematic review. Therefore, the research design for this study comprises of five phases which includes the specification of inclusion and exclusion criteria, presenting of search strategies and data sources, quality assessment, and data coding and analysis, and lastly findings. The research design of this review study is shown in Fig.  2 .

Research design for SLR

Figure  2 depicts the research design for this study, where each phase is presented in the subsequent sub-sections.

3.1 Inclusion and Exclusion Criteria

The inclusion and exclusion criteria (Table 1 ) and quality assessment criteria (see Table 2 ) are employed as the sampling/selection methods used to select the articles involved in this study. The inclusion and exclusion criteria are defined in Table 1 .

3.2 Search Strategies and Data Sources

The articles involved in this study were retrieved through a comprehensive search of prior studies via online databases which included Google Scholar, ScienceDirect, Emerald, IEEE, Sage, Taylor & Francis, Inderscience, Springer, and Wiley. The search was undertaken in December 2018 and March 2020. The search terms comprise the keywords ((“blended learning practices” OR “blended learning variables” OR “blended learning factors” OR “blended learning constructs”) AND (“implementation” OR “adoption” OR “approach” OR “model” OR “framework” OR “theory”)) AND (“components” OR “elements”)). The mixture of the keywords is a crucial step in any systematic review as it defines articles that will be retrieved.

Figure  3 depicts the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flowchart which was employed for searching and refining of the articles as previously utilized by Al-Emran et al. ( 2018 ). The search output presented 388 articles using the above stated keywords. 93 articles were establish as duplicates, as such were removed. Therefore, resulted to 302 articles. The authors checked the articles against the inclusion and exclusion criteria and added 12 new articles based on snowballing techniques which was used to get more articles from the references of 82 studies. Accordingly, 94 research articles meet the inclusion criteria and were included in the review process. Additionally, four studies (Kitchenham and Charters 2007 ; Anthony et al. 2017 , b ; Al-Emran et al. 2018 ) were included in the reference since they discuss SLR process.

PRISMA flowchart for the selected articles

3.3 Quality Assessment

One of the vital determinants that are required to be checked along with the inclusion and exclusion criteria is the quality assessment. To this end, a quality assessment checklist which comprises of “10” criteria was designed and employed as a means for evaluating the quality of the studies selected (n = 94) (see Fig.  3 ). The quality assessment checklist is shown in Table 2 . The checklist was adapted from recommendation from (Kitchenham and Charters 2007 ). Accordingly, the question was measured based on a 3-point scale which ranges from, 1 point being assigned for “Yes”, 0 point for “No”, and 0.5 point for “Partially”. Hence, each article score ranges from 0 to 10, where a study that attains higher total score, possess the capability to provide addresses the specified research questions. Table 11 in appendix shows the quality assessment results for all the 94 studies. Respectively, it is apparent that the selected studies have passed the quality assessment, which indicates that all the articles are eligible to be utilized for further meta-analysis.

3.4 Data Coding and Analysis

The characteristics related to the research methodology outcome were coded to include purpose of research, (BL adoption constructs and factors or BL implementation practice), research approach (e.g., literature review, conceptual, survey questionnaire, case study interviews, or experimental), country, context (e.g., student, lecturer and/or administrator), and model/framework or theory employed (e.g., Technology Acceptance Model (TAM), information system success model, the Unified Theory of Acceptance and Use of Technology (UTAUT), Diffusion of Innovations theory (DoI), Adhoc, etc.). In between the data analysis procedure, the articles that did not directly describe BL adoption model variables and implementation practices were excluded from the synthesis.

4 Findings and Discussion

Based on the selected 94 studies published in regard to BL adoption and implementation from 2004 to 2020, this review reports the findings of this systematic review in relation to the specified six research questions.

4.1 RQ1: What are the Research Methods, Countries, Contexts, and Publication Year of Selected BL Studies?

With regard to the first research question, the findings for distribution of studies related to BL adoption and implementation in higher education based on year of publication is presented in Fig.  4 . As shown, the studies are ranged from 2004 to 2020. Findings from Fig.  4 indicate that there seems to be an increase in studies on BL over the last few years as seen from 2004 to 2020, with 2018 being the highest with publications on BL adoption and implementation with 17 studies published. It is evident that the frequency of these publications in 2018 could be accredited to the fact that the intensity of BL implementation in 2018 across higher education has improved mainly in developed and developing countries across the world.

Distribution of selected BL studies in terms of years

Considering the research methodology applied in the 94 BL studies, findings from Fig.  5 show that questionnaire survey is the most employed method for data collection (N = 49, 62%), followed by studies that were conceptual by design with (N = 14, 16%). Next, is studies that adopted mixed method both survey and interview with (N = 11, 13%) and studies that are qualitative in nature as case study/interview with (N = 8, 9%). For the remaining studies (N = 5, 5%) employed experimental using LMS dataset, (N = 4, 4%) conducted literature review, and lastly only (N = 1, 1%) study deployed a mixed experimental and survey approach. These findings are analogous with the prior review studies conducted by (Holton III et al. 2006 ; Kumara and Pande 2017 ) who discussed that quantitative studies were the main approach employed in prior BL studies. Furthermore, this finding is consistent with the fact that surveys are considered as the most suitable tool to collect data in validating constructs/factors in developed BL adoption model in investigating students and lecturers’ perceptions towards BL practice in higher education (Ghazali et al. 2018 ; Ismail et al. 2018b ).

Distribution of selected BL studies in terms of research methods

With regard to the 94 BL studies country distribution, findings from Fig.  6 shows research related to BL adoption in higher education. Accordingly, most of the studies are conducted in Malaysia (N = 28), this is based on the fact that the Malaysia ministry of education initiated an educational blueprint for all higher education to adopt BL from 2015 to 2022. Therefore, there were several studies that proposed models to examine BL adoption in universities in Malaysia context. Next, research articles related to BL adoption was carried out in United States of America with (N = 11), and Australia (N = 10) and United Kingdom with (N = 7), followed by Turkey with (N = 4), Canada, Indonesia, and Spain with (N = 3) respectively. Additionally, Fig.  6 indicates that (N = 2) studies were conducted in Norway, Dubai, UAE, India, Singapore, Saudi Arabia, and Taiwan. Lastly, (N = 1) study was each conducted in Greece, Germany, Philippines, South Korea, The Netherlands, Thailand, Vietnam, Belgium, Bulgaria, China, Poland, Israel, Morocco, Colombia, Sri Lanka, and Ghana. This finding also suggest that most of the first researchers of BL adoption such as Garrison and Kanuka ( 2004 ), Graham et al. ( 2013 ), Poon ( 2014 ) and Porter and Graham ( 2016 ) are from USA, Canada, Australia and UK who are one of the most cited researchers in BL practice in higher education as compared to other regions.

Distribution of selected BL studies in terms of countries

Considering the selected studies context distribution of BL adoption in higher education findings from Fig.  7 indicate that (N = 59, 62%) studies mainly examined BL adoption by considering students perspective. This finding is consistent with results from prior studies (Wai and Seng 2013; Rahman et al. 2015 ) which advocated for the need for developing a model of measuring student satisfaction, perception (So and Brush 2008 ), commitment (Wong et al. 2014 ), effectiveness (Wai and Seng 2015 ) in the BL. In addition, findings from Fig.  7 reveal that (N = 9, 10%) studies mainly examined BL adoption by considering lecturers perspective. This finding is very consistent with results from the literature (Wong et al. 2014 ; Zhu et al. 2016 ), where the authors mentioned the need for a study to investigate the current level of adoption of BL among the academicians to identify the factors that influence BL adoption.

Distribution of selected BL studies context

Furthermore, the findings suggest that (N = 7, 8%) studies mainly examined BL adoption by considering administrative perspective. Similarly, this finding is analogous with results from qualitative studies conducted by prior researchers (Koohang, 2008 ; Graham et al. 2013 ; Porter et al. 2016 ; Bokolo Jr et al. 2020 ) which revealed that there are limited studies that explored policy and governance issues related BL adoption. Additionally, findings from Fig.  7 show that (N = 10, 10%) studies that concurrently examined BL in the context of students and lecturers, this aligns with findings presented by Brahim and Mohamad ( 2018 ); Edward et al. ( 2018 ) where the authors called for the need for empirical evidence on BL implementation to improve academic activities. Lastly, (N = 9, 10%) studies investigated BL in the context of student, lecturer, and administrators. This finding suggests that there are limited studies that examine students, lectures and administrators simultaneously as mentioned by (Machado 2007 ; Wong et al. 2014 ; Bokolo Jr et al. 2020 ). Accordingly, this review presents the constructs and factors that influence BL adoption from the perspective of students, lecturers, and administrators in higher education.

4.2 RQ2: Which BL Studies Proposed Model Related to BL Adoption in Higher Education?

Several studies have been carried out directed towards investigating the adoption of BL in higher education. Thus, Table 3 shows that out of the selected 94 studies only 51 studies developed models to examine BL where each study is compared based on the authors, contribution, purpose and identified factors/attributes and methods.

Based on the selected 51 BL studies that develop a research model to examine BL adoption in higher education, the review indicates that none of the studies is concerned with BL practices to be implemented in higher education, they are mainly concerned about BL adoption factors/attributes. As seen in Fig.  8 out of the reviewed 51 BL studies that developed models to examine BL adoption. The results suggest that survey questionnaire was most employed, whereas experimental and survey was least employed to validate the developed models. Also, Fig.  9 presents the clustered of issues addressed in the reviewed 51 BL studies. The identified factors/attributes derived from the reviewed 51 BL studies are presented in Fig.  10 and further discussed in Tables 6 , 7 and 8 .

Distribution of the reviewed 51 BL studies that developed BL adoption models

Clustering of issues addressed in the reviewed BL adoption studies

Identified factors/attributes derived in the reviewed BL adoption studies

4.3 RQ3: Based on RQ2 What are the Theories, Location, and Context of the Selected BL Studies?

Among the selected 51 BL studies, this sub-section presents prior theories that have been utilized to examine BL adoption in higher education. Moreover, the location and BL context of the 51 BL studies are presented as seen in Table 4 .

Findings from Table 4 and Fig.  11 indicate that out of the reviewed 51 BL studies, (N = 37, 72%) studies investigated BL by considering the students context similar to previous studies Tuparova and Tuparov ( 2011 ); Roszak et al. ( 2014 ), while (N = 2, 4%) studies examined BL by considering only lecturers’ context. Besides, (N = 4, 8%) studies only examined administration context analogous with prior study Mercado ( 2008 ), while another (N = 6, 12%) studies examined BL by considering the students and lecturers context similar to prior studies Maulan and Ibrahim ( 2012 ); Mohd et al. ( 2016 ). Lastly, (N = 2, 4%) studies examined BL by considering the students, lecturers and administration context analogous to research conducted by Mercado ( 2008 ); Anthony et al. ( 2019 ). Hence, it is evident that there are fewer studies that investigated BL adoption by concurrently exploring students, lecturers and administration viewpoint. Thus, this review aims to address this limitation by reviewing theoretical foundation of BL adoption and implementation in the lens of students, lecturers and administration.

Selected BL adoption studies context distribution

4.4 RQ4: Based on RQ3 What are the Constructs of the Identified Theories Employed to Explore BL Adoption in Higher Education?

This sub-section reviews the constructs of theories employed by the selected 51 BL studies in developing their model as seen in Table 5 .

Based on Tables 4 and 5 , Fig.  12 depicts the frequency of how many times each theory has been employed by prior BL studies. Findings from theories employed show that ad hoc is the most employed approach with (N = 23, 42%) studies, followed by TAM with (N = 7, 13%) studies, IS success model and UTAUT with (N = 4, 7%) studies individually, and DoI with (N = 3, 5%) studies, whereas the other theories were adopted by (N = 1, 2%) study respectively.

Distribution of BL studies in terms of adopted theories

4.5 RQ5: What are the Constructs and Factors that Influence Students, Lecturers and Administration towards Adopting BL?

The constructs and factors related to the adoption of BL by students, lecturers and administrators are shown in Fig.  13 and described in Table 6 .

Constructs and factors related to BL adoption in higher education

Tables 6 , 7 and 8 describes the derived constructs for students, lecturers, and administration related to BL adoption in higher education. BL adoption cannot be attained by only integrating online and face-to-face teaching modes (Azizan 2010 ). Thus, there is need to identify the constructs that influence students, lecturer, and administration in adopting BL practices to be implemented that play an important role in ensuring successful BL experience in higher education (Graham 2013 ; Güzer and Caner 2014 ). On this note, academicians such as Machado ( 2007 ); Wong et al. ( 2014 ); Kumara and Pande ( 2017 ); Bokolo Jr et al. ( 2020 ) highlighted that successful implementation of BL initiatives requires an alignment between administrative, lecturers, students’ educational goals. According to Dakduk et al. ( 2018 ); Anthony et al. ( 2019 ) it is importance to examine constructs related to human computer interaction to assess which constructs contributes to realizing the desired teaching and learning objectives while engaging the lecturers and students. Therefore, this study explores the BL practices to be implemented by students and lecturers in higher education as seen in Figs.  14 and 15 .

BL practice implementation for students in higher education

BL practice implementation for lecturers in higher education

4.6 RQ6: What are the Practices Involved for BL Implementation in Higher Education?

The practice to be carried out by students for implementing BL in higher education is shown in Fig.  14 .

Figure  14 depicts BL practice implementation for students in higher education. According to Kaur and Ahmed ( 2006 ); Kaur ( 2013 ) the recommended balance of BL activities for successful delivery is 80% online learning (activities, information, resources, assessment and feedback) followed by 20% classroom instruction (face to face) that is aligned to the online teaching content. Similarly, Ginns and Ellis ( 2007 ) argued that for an effective BL initiative it is required to achieve a blend of 29–30% face to face and 79–80% on-line teaching delivery. This is in line with findings from previous studies (Graham et al. 2013 ; Bokolo Jr et al. 2020 ), which states that there is need for policies showing clear decrease of face to face classroom hours and increasing online learning as a strategy to enhance BL implementation in higher education (Park et al. 2016 ). Further description of BL implementation for students is discussed in Table 9 .

Figure  15 depicts BL practice implementation for lecturers in higher education. The BL practice is based on the Technology, Pedagogy, and Content Knowledge (TPACK) framework proposed by Koehler and Mishra ( 2009 ). TPACK aimed address issues faced by how lecturers can integrate technology into their current teaching (Wang et al. 2004 ; Sahin 2011 ). Thus, TPACK offers a method that indulgences teaching as collaboration between what lecturers know and how they teach and apply what they already know uniquely through BL implementation in the contexts of physical and online classes (Graham et al. 2009 ; Koehler and Mishra 2009 ). Further description of TPACK the components in relation to BL implementation is discussed in Table 10 .

5 Implications for Theory, Methodology and Pedagogical Practice

Findings from this study offer implications for theory, methodology and pedagogical practice for higher education towards adopting BL.

5.1 Implications for Theory

Theoretically, this study identifies the factors that influence students, lecturers and administrators’ towards adopting BL. Our findings provide insight by revealing factors for higher education to better recognize how BL can be delivered towards the development of students’ learning effectiveness and also offering in-depth understanding of BL and its efficiency in order to improve students’ competence. The identified factors can be employed by institutions to assess students, lecturers and administrators’ perception towards BL and can be used to inform government policy making regarding BL development. Besides, this study also indicates that the lecturer’s attitude, teaching style, and acceptance toward BL are important in motivating the students to adopt BL. The lecturer’s attitude toward students and his/her level of responsiveness and communication are important factors that motivate students in BL environment. The findings emphasized the importance of administrative commitment towards BL adoption, showing that the purpose, advocacy and definition initiated towards BL have a strong impact on both learning and teaching effectiveness. The findings provide theoretical support to determine the relationship among the constructs and factors of BL adoption for students, lecturers and administrators (see Fig.  13 ) towards F2F and online learning.

5.2 Implications for Methodology

Based on the TPACK framework, this study provides lecturers with understanding of students' perspective on BL in helping them to reflect on their role in improving their current pedagogy, technological infusion, and syllabus design to enhance student learning and teaching outcome. Decision makers in higher education can utilize findings from this study to improve their understanding of the factors that impacts students, lecturers and administrators’ perception towards BL adoption. Respectively, given the different perspectives of students, lecturers and administrators it is mandatory for policy makers in higher education involved in the implementation of BL to deliberate on the perspectives of all stakeholders. Respectively, findings from this study significantly provide an outline for Ministry of Education across the world towards fostering BL as a teaching and learning approach for academic staffs in higher education. The BL practices for students (see Fig.  14 ) and strategies to be implemented by lecturers (see Fig.  15 ) can be integrated to the existing pedagogical polices to improve the significance of BL as one of the methods in learning and teaching. For universities and academicians, findings from this study suggest that BL serves as a substitute to learning and teaching from the traditional perspective to enhance the quality of teaching and learning of students in achieving better performance.

5.3 Implications for Pedagogical Practice

This study contributes to the acknowledgment of BL as a medium to support teaching and learning approach. The findings describing how BL practice can be implemented by students as seen in Sect.  4.6 (Fig.  14 ). Practically, findings from this study can be useful in the preparation of the best practice to support lecturers in teaching and implementing inventive approaches that promotes BL to enhance teaching and learning outcomes to be used as the reference for the arranging methodologies to embrace BL in higher education. Findings from this study indicate that BL practices derived from the literature which comprises of face-to-face, activities, information, resources, assessment, and feedback to be deployed by educators to design suitable learning policies in order to support students towards improving learning. These findings provide guidelines on the design and implementation of BL practice. This study suggests that for BL practice to be successfully implemented the decision of lecturers are determined by the ease with which online course services are managed. Thus, the availability of computer hardware and software resources, pedagogical support, financial support, and promotion consideration should be provided by institutions management. For administrators this study provides a policy roadmap to adopt BL in higher education.

6 Conclusion, Limitations, and Future Works

Review of prior studies on BL offer valuable insight regarding research related to BL practice in higher education. Nonetheless, these review studies ignored examining BL adoption and implementation in regard to students, lecturers and administrators simultaneously. Accordingly, this study conducted a systematic literature review for prior BL adoption model proposed related to theories employed in the model to investigate BL adoption in higher education. This study also identified the constructs and factors that influence students, lecturers and administration towards adopting BL studies and lastly derived the practices involved for BL implementation for students and lecturers in higher education with the aim of providing meta-analysis of the current studies and to present the implications from the review. Respectively, this paper extends the body of knowledge in BL studies by presenting 7 new findings. First, the review reveal that ad hoc approach is the most employed method by prior studies in developing research model to investigate BL adoption in higher education, followed by TAM, and then IS success model, then is UTAUT, and lastly DoI theory.

Secondly, findings show that questionnaire surveys were the most employed research methods for data collection utilized by prior BL studies in higher education. Third, the findings reveal that BL model adoption studies were carry out in Malaysia and USA, this is followed by Australia, UK, Canada, respectively among the other countries. Fourth, most of the BL studies were recurrently conducted towards examining BL in students’ context, followed by lecturers’ context, correspondingly among the other contexts. Fifth, with regard to publication year, BL studies have experienced vast attraction over the years (2016 to 2019) from many academicians who contributed to investigating BL adoption and implementation in higher educational context, where our findings observed an increase of 19 publications in 2018 (see Fig.  4 ) representing the highest frequency of the total studies. Sixth, this review also presents 51 prior studies that developed model relating to the adoption of BL in higher educational domain and further identify the constructs/factors that influence the perception of students, lecturers, and administration readiness towards BL adoption. Seventh, findings from this review present the BL practice to be implemented by students and lecturers in higher education. To that end, the identified constructs/factors that influence BL adoption and the derived BL practices implementation can be used to conceptualize and develop a model to examine student, lecturers, and administrators concurrently towards BL adoption and implementation in higher education.

Despite the aforementioned contributions, this study has a few limitations. First, the reviewed BL studies comprises of studies related to BL adoption and implementation approaches, models, and frameworks. BL readiness and effectiveness were not investigated in this current study. Secondly, this study mainly focused on popular online databases for collecting articles (i.e., ScienceDirect, Sage, Emerald, Inderscience, Wiley, Google Scholar, Springer, Taylor & Francis, and IEEE). Given that, the databases may not provide all relevant studies published on BL adoption and implementation. Thirdly, no theoretical model was proposed with hypotheses for further validation. Future studies could examine BL readiness and effectiveness from student, lecturers, and administrator’s perspective by developing a research model with hypotheses. The model will be evaluated using survey questionnaire since it’s the most widely employed methodology as seen in Fig.  5 and 8 . Further research could also extent this study by including more BL studies from other online libraries which includes Web of Science, Scopus, etc. to investigate BL in its broad sense and how it affects students, lecturers and administration in a particular country or region.

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Open Access funding provided by NTNU Norwegian University of Science and Technology (incl St. Olavs Hospital - Trondheim University Hospital) This study was supported by Universiti Malaysia Pahang Malaysia Grant No. RDU180702.

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Adzhar Kamaludin, Awanis Romli, Anis Farihan Mat Raffei, Danakorn Nincarean A. L. Eh Phon, Aziman Abdullah & Gan Leong Ming

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Anthony, B., Kamaludin, A., Romli, A. et al. Blended Learning Adoption and Implementation in Higher Education: A Theoretical and Systematic Review. Tech Know Learn 27 , 531–578 (2022). https://doi.org/10.1007/s10758-020-09477-z

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Accepted : 26 September 2020

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DOI : https://doi.org/10.1007/s10758-020-09477-z

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