Comparing online and blended learner's self-regulated learning strategies and academic performance
TL;DR: The results show that online students utilised SRL strategies more often than blended learning students, with the exception of peer learning and help seeking, and key SRL predictors of academic performance were largely equivalent between online and blendedlearning students.
Abstract: The existing literature suggests that self-regulated learning (SRL) strategies are relevant to student grade performance in both online and blended contexts, although few, if any, studies have compared them. However, due to challenges unique to each group, the variety of SRL strategies that are implicated, and their effect size for predicting performance may differ across contexts. One hundred and forty online students and 466 blended learning students completed the Motivated Strategies for Learning Questionnaire. The results show that online students utilised SRL strategies more often than blended learning students, with the exception of peer learning and help seeking. Despite some differences in individual predictive value across enrolment status, the key SRL predictors of academic performance were largely equivalent between online and blended learning students. Findings highlight the relative importance of using time management and elaboration strategies, while avoiding rehearsal strategies, in relation to academic subject grade for both study modes.
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TL;DR: A systematic review of literature was conducted with the aim of identifying the challenges in the online component of blended learning from students, teachers and educational institutions perspectives.
Abstract: Blended learning is widely regarded as an approach that combines the benefits afforded by face-to-face and online learning components. However, this approach of combining online with face-to-face instructional components have raised concerns over the years. Several studies have highlighted the overall challenges of blended learning mode of instruction as a whole, but there has been no clear understanding of the challenges that exist in the online component of blended learning. Thus, a systematic review of literature was conducted with the aim of identifying the challenges in the online component of blended learning from students, teachers and educational institutions perspectives. Self-regulation challenges and challenges in using learning technology are the key challenges that students face. Teachers challenges are mainly on the use of technology for teaching. Challenges in the provision of suitable instructional technology; and effective training support to teachers are the main challenges faced by educational institutions. This review highlights the need for further investigations to address students, teachers and educational institutions challenges in blended learning. In addition, we proposed some recommendations for future research.
463 citations
Cites background from "Comparing online and blended learne..."
...Several studies have reported the problems that students e.g. (Broadbent, 2017; Prasad, Maag, Redestowicz, & Hoe, 2018), teachers e.g. (Cuesta Medina, 2018; Ocak, 2011) and educational institutions e.g. (Cuesta Medina, 2018) encounter with the online component of blended learning....
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...From the results in Table 1 (AlJarrah et al., 2018; Broadbent, 2017; Chuang et al., 2018; J. C. Y.; Sun et al., 2017), have identified self-regulation challenges in the form of procrastination, whereby students face difficulty in proper self-regulation, which results to poor time management and…...
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...…of procrastination (AlJarrah, Thomas, & Shehab, 2018; Broadbent, 2017; Maycock, Lambert, & Bane, 2018; J. C. Y.; Sun, Wu, & Lee, 2017), improper time management (Broadbent, 2017; Zacharis, 2015) and improper utilization of online peer learning and online help-seeking strategies (Broadbent, 2017)....
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...Because, if done well, the approach combines the benefits afforded by both face-toface and online learning mode of instructions (Broadbent, 2017)....
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...…students resort to seeking online help from other unreliable and informal sources such as ‘how-todo’ manuals, search engines (e.g. Google), reading and studying online posts, reviewing conversations or chats on discussion forums, watching videos from YouTube etc. as asserted by (Broadbent, 2017)....
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TL;DR: It is concluded that COVID-19 confinement changed students’ learning strategies to a more continuous habit, improving their efficiency.
Abstract: This study analyzes the effects of COVID-19 confinement on the autonomous learning performance of students in higher education. Using a field experiment with 458 students from three different subjects at Universidad Autonoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that had their face-to-face activities interrupted because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students' performance. This effect is also significant in activities that did not change their format when performed after the confinement. We find that this effect is significant both in subjects that increased the number of assessment activities and subjects that did not change the student workload. Additionally, an analysis of students' learning strategies before confinement shows that students did not study on a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students' learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students' assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performance.
395 citations
TL;DR: In this paper, a systematic literature review (SLR) was conducted to identify the research topics, most relevant theories, most researched modalities, and the research methodologies used for e-learning.
Abstract: The concept of e-learning is a technology-mediated learning approach of great potential from the educational perspective and it has been one of the main research lines of Educational Technology in the last decades The aim of the present systematic literature review (SLR) was to identify (a) the research topics; (b) the most relevant theories; (c) the most researched modalities; and (d) the research methodologies used To this end, the PRISMA protocol was followed, and different tools were used for the bibliographic management and text-mining The literature selection was carried out in three first-quartile journals indexed in JCR-SSCI specialized in Educational Technology A total of 248 articles composed the final sample The analysis of the texts identified three main nodes: (a) online students; (b) online teachers; and (c) curriculum-interactive learning environments It was revealed that MOOC was the most researched e-learning modality The Community of Inquiry and the Technological Acceptance Model, were the most used theories in the analyzed studies The most frequent methodology was case study Finally, the conclusions regarding the objectives of our SRL are presented: Main themes and research sub-themes, most researched e-learning modality, most relevant theoretical frameworks on e-learning, and typologies of research methodologies
216 citations
TL;DR: There is still a need for more research on organization level topics such as leadership, policy, and management and access, culture, equity, inclusion, and ethics and also on online instructor characteristics.
Abstract: Systematic reviews were conducted in the nineties and early 2000's on online learning research. However, there is no review examining the broader aspect of research themes in online learning in the last decade. This systematic review addresses this gap by examining 619 research articles on online learning published in twelve journals in the last decade. These studies were examined for publication trends and patterns, research themes, research methods, and research settings and compared with the research themes from the previous decades. While there has been a slight decrease in the number of studies on online learning in 2015 and 2016, it has then continued to increase in 2017 and 2018. The majority of the studies were quantitative in nature and were examined in higher education. Online learning research was categorized into twelve themes and a framework across learner, course and instructor, and organizational levels was developed. Online learner characteristics and online engagement were examined in a high number of studies and were consistent with three of the prior systematic reviews. However, there is still a need for more research on organization level topics such as leadership, policy, and management and access, culture, equity, inclusion, and ethics and also on online instructor characteristics.
211 citations
Cites background from "Comparing online and blended learne..."
...…(Artino & Stephens, 2009), have academic self-efficacy (Cho & Shen, 2013), have grit and intention to succeed (Wang & Baker, 2018), have time management and elaboration strategies (Broadbent, 2017), set goals and revisit course content (Kizilcec et al., 2017), and persist (Glazer & Murphy, 2015)....
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TL;DR: Challenges that arise in the process of extracting theory-based patterns from observed behaviour are discussed, including analytic issues and limitations of available trace data from learning platforms.
200 citations
Cites background or methods from "Comparing online and blended learne..."
...First, the Only Videolecture interaction pattern was associated with three SRL strategies in the literature: studying (Garavalia & Gredler, 2002), rehearsing (Broadbent, 2017), and repeating (Sonnenberg & Bannert, 2015)....
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...Several studies have demonstrated a positive relationship between the use of SRL strategies in online environments and academic achievement (Broadbent & Poon, 2015; Broadbent, 2017; Richardson, Abraham, & Bond, 2012; Robbins et al., 2004; Wang, Shannon, & Ross, 2013)....
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...High-SRL Learners that complete the course spend periods of time between 1 and 5 minutes in this sequence pattern, which implies a kind of learning involving recall of the information rather than an effort to achieve a deep understanding of the content (Broadbent, 2017)....
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...The interaction pattern Only Video-lecture could be related with three SRL strategies: (1) Study SRL strategy (Garavalia & Gredler, 2002), (2) Rehearsal SRL strategy (Broadbent, 2017) and (3) Repeating SRL strategy (Sonnenberg & Bannert, 2015)....
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References
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TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...
76,383 citations
"Comparing online and blended learne..." refers methods in this paper
...…acceptability of fit for the model in which parameters were constrained to equality: non-significant chi square value, Comparative Fit Index (CFI) >.95, Root Mean Square Error of Approximation (RMSEA) <.06, and Standardized Root Mean Square Residual (SRMR) <.08 (Byrne, 2012; Hu & Bentler, 1999)....
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Book•
01 Jan 1983
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs
53,113 citations
"Comparing online and blended learne..." refers methods in this paper
...As the remaining variables had less than 5% data missing, expectation maximisation algorithm was applied to replace missing values (Tabachnick & Fidell, 2013)....
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Book•
21 Jul 2011
TL;DR: Structural Equation Models: The Basics using the EQS Program and testing for Construct Validity: The Multitrait-Multimethod Model and Change Over Time: The Latent Growth Curve Model.
Abstract: Psychology is a science that advances by leaps and bounds The impulse of new mathematical models along with the incorporation of computers to research has drawn a new reality with many methodological progresses that only a few people could imagine not too long ago Such progress has no doubt revolutionized the panorama of research in the behavioral sciences Structural Equation Models are a clear example of this Under this label are usually included a series of state-of-the-art multivariate statistical procedures that allow the researcher to test theoryguided hypotheses with clearly confi rmatory ends as well as to establish causal relations among variables Confi rmatory factor analysis, the study of measurement invariance, or the multitraitmultimethod models are some of the procedures that stem from this methodology In this sense, it would be diffi cult to fi nd a scientifi c journal that publishes empirical works in psychology that does not address some of these issues, so their current transcendence is undeniable The manual written by the Full Professor of the University of Ottawa, Barbara M Byrne, is a link in a series of books that address this topic Throughout her long academic trajectory, Professor Byrne developed interesting and popular work focused on bringing the researcher and the professional layman—and not so layman—closer to the diverse statistical programs available on the market for data analysis from the perspective of structural equation models (ie, LISREL, AMOS, EQS) (Byrne, 1998, 2001, 2006) Bearing this in mind, the main goal of this work is to introduce the reader to the basic concepts of this methodology, in a simple and entertaining way, avoiding mathematical technicisms and statistical jargon For this purpose, we used the statistical program Mplus 60 (Muthen & Muthen, 2007-2010), an extremely suggestive software that incorporates interesting applications The authoress provides a practical guide that leads the reader through illustrative examples of how to proceed step by step with the Mplus, from the initial specifi cations of the model to the interpretation of the output fi les On the one hand, we underline that the data used proceed from prior investigations and can be consulted in the Internet, offering the reader the possibility of practicing with them (http://wwwpsypresscom/sem-with-mplus/ datasets/); on the other hand, updating the information with novel and apt bibliographic references allows the reader to study in more depth the diverse topics that are presented in the manual, if he or she so desires The book consists of four sections, with a total of 12 chapters The fi rst section, Chapters 1 and 2, addresses introductory terms related to structural equation models and working with the Mplus program at a user-level The second unit focuses on data analysis with a single group In Chapter 3, the factor validity of the self-concept is tested by means of confi rmatory factor analysis In Chapter 4, the authoress performs a fi rst-order confi rmatory factor analysis, in which she examines the validity of the scores of the Maslach Burnout Inventory (MBI) in a sample of teachers In Chapter 5, the internal structure of the scores on the Beck Depression Inventory-II is analyzed by means of second-order confi rmatory factor analysis in a sample of Chinese adolescents In the next chapter, the complete model of structural equations is tested, and the authoress examines the causal relation established between diverse variables (ie, work climate, self-esteem, social support) and Burnout The third section of the manual is, in my opinion, the most interesting, not only because of the expansion of the study of measurement invariance in recent years but also because of the expansion it may possibly have in the future In this section, Professor Byrne goes into multigroup comparisons Specifi cally, in Chapter 7, she examines the factor equivalence of the MBI in two samples of teachers by means of the analysis of covariance structures In this chapter, she introduces relevant concepts, such as types of invariance (confi gural, metric, and strict) or the invariance of partial measurement In Chapter 8, she also analyzes measurement invariance, using for this purpose the analysis of mean and covariance structures This analysis, in comparison to the analysis of covariance structures, allows contrasting the latent means of two or more groups With this goal, she verifi es whether there is measurement invariance between the scores on the Self-description Questionnaire-I in Nigerian and Australian adolescents In Chapter 9, she proposes a complete model of structural equations in which she tests the causal structure through the procedure of cross validation Lastly, in the fourth section, she reveals three very interesting topics, that are also up-to-date and that, to some degree, go beyond the initial goal of the book, such as the multitrait-multimethod models, latent growth curves, and multilevel models Summing up, the work “Structural Equation Modeling with Mplus: Basic concepts, applications, and programming” is of enormous interest and utility for all professionals of psychology and related sciences who, without having exhaustive knowledge of the details of structural equation models, wish to test their hypothetical models by means of the Mplus program No doubt, this is a reference manual, a must-read that is accessible and that has a high degree of methodological rigor We hope that the readers
16,616 citations
"Comparing online and blended learne..." refers methods in this paper
...In contrast, a non-significant chi square difference between the models suggests that a single model is sufficient to summarize relationships between SRL strategies and performance for all participants, regardless of group membership (blended learning and online group; Byrne, 2012)....
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...…acceptability of fit for the model in which parameters were constrained to equality: non-significant chi square value, Comparative Fit Index (CFI) >.95, Root Mean Square Error of Approximation (RMSEA) <.06, and Standardized Root Mean Square Residual (SRMR) <.08 (Byrne, 2012; Hu & Bentler, 1999)....
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Book•
22 Nov 2017
TL;DR: The Fourth Edition of Andy Field's Discovering Statistics Using SPSS 4th Edition focuses on providing essential content updates, better accessibility to key features, more instructor resources, and more content specific to select disciplines.
Abstract: Unrivalled in the way it makes the teaching of statistics compelling and accessible to even the most anxious of students, the only statistics textbook you and your students will ever need just got better! Andy Field's comprehensive and bestselling Discovering Statistics Using SPSS 4th Edition takes students from introductory statistical concepts through very advanced concepts, incorporating SPSS throughout. The Fourth Edition focuses on providing essential content updates, better accessibility to key features, more instructor resources, and more content specific to select disciplines. It also incorporates powerful new digital developments on the textbook's companion website(visit sagepub.com for more information). WebAssign The Fourth Edition will be available on WebAssign, allowing instructors to produce and manage assignments with their studnets online using a grade book that allows them to track and monitor students' progress. Students receive unlimited practice using a combination of approximately 2000 multiple choice and algorithmic questions. WebAssign provided students with instant feedback and links directly to the accompanying eBook section where the concept was covered, allowing students to find the correct solution. SAGE MobileStudy SAGE MobileStudy allows students equipped with smartphones and tablets to access select material, such as Cramming Sam's Study Tips, anywhere they receive mobile service. With QR codes included throughout the text, it's easy for students to get right to the section they need to study, allowing them to continue their study from virtually anywhere, even when they are away from thier printed copy of the text. Click here to preview the MobileStudy site (available late spring 2013). Education and Sport Sciences instructor support materials with enhanced ones for Psychology, Business and Management and the Health sciences make the book even more relevant to a wider range of subjects across the social sciences and where statistics is taught to a cross-disciplinary audience. Major Updates to the 4th Edition Fully compatible with recent SPSS releases up to and including version 20.0 Exciting new characters, including statistical cult leader Oditi, who provides students access to interesting and helpful video clips to illustrate statistical and SPSS concepts, and Confusious, who helps students clarify confusing quantitative terminology New discipline specific support matierlas have been added for Education, Sports Sciences, Psychology, Business & Management, and Health Sciences, making the book even more relevant to a wider range of subjects across the Social, Behavioral, and Health Sciences is taught to an interdisciplinary audience. An enhanced Companion Website (available late spring 2013) offers a wealth of material that can be used in conjunction with the textbook, including: PowerPoints Testbanks Answers to the Smart Alex tasks at the end of each chapter Datafiles for testing problems in SPSS Flashcards of key concepts Self-assessment multiple-choice questions Online videos of key statistical and SPSS procedures
10,316 citations
"Comparing online and blended learne..." refers background in this paper
...Partial eta squared values greater than .01 were considered small, >.06 moderate, and >.14 large effects (Field, 2013)....
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Book•
01 Jan 2014
TL;DR: The Taxonomy of Educational Objectives as discussed by the authors is a taxonomy of educational objectives that is based on the concepts of knowledge, specificity, and problems of objectives, and is used in our taxonomy.
Abstract: List of Tables and Figures. Preface. Foreword. SECTION I: THE TAXONOMY, EDUCATIONAL OBJECTIVES AND STUDENT LEARNING. 1. Introduction. 2. The Structure, Specificity, and Problems of Objectives. SECTION II: THE REVISED TAXONOMY STRUCTURE. 3. The Taxonomy Table. 4. The Knowledge Dimension. 5. The Cognitive Process Dimension. SECTION III: THE TAXONOMY IN USE. 6. Using the Taxonomy Table. 7. Introduction to the Vignettes. 8. Nutrition Vignette. 9. Macbeth Vignette. 10. Addition Facts Vignette. 11. Parliamentary Acts Vignette. 12. Volcanoes? Here? Vignette. 13. Report Writing Vignette. 14. Addressing Long-standing Problems in Classroom Instruction. APPENDICES. Appendix A: Summary of the Changes from the Original Framework. Appendix B: Condensed Version of the Original Taxonomy of Educational Objectives: Cognitive Domain. References. Credits. Index.
9,708 citations