Effectiveness of e-learning: the mediating role of student engagement on perceived learning effectiveness
TL;DR: A research model using personal and environmental factors to understand PLE through the lens of SCT is developed and empirically validates it and it is found that the PLE is positively related to student marks.
Abstract: PurposeThis study extends the literature on the effectiveness of e-learning by investigating the role of student engagement on perceived learning effectiveness (PLE) in the context of Indian higher education. Further, the impact of personal factors (Internet self-efficacy (ISE)) and environmental factors (information, system and service quality parameters) on various dimensions of student engagement (behavioral, emotional and cognitive) is studied through the lens of social cognitive theory (SCT).Design/methodology/approachAn online management information systems (MIS) course is delivered to a batch of 412 postgraduate students. An online survey was conducted to measure the factors affecting their PLE. In addition to the survey, a summative assessment is conducted to evaluate the students in terms of their marks to assess their achievements (actual learning). Covariance-based structural equation modeling (CB-SEM) is used to validate the developed research model.FindingsIt is discovered that the IS (information system) quality parameters (environmental factors) positively impact PLE. The ISE affects the PLE through the mediating effect of all the dimensions of student engagement. Furthermore, there exists a positive relationship between PLE and student marks.Originality/valueThis study develops a research model using personal and environmental factors to understand PLE through the lens of SCT and then empirically validates it. The psychological process from the students' ISE to the PLE is explained through the mediating effects of various dimensions of engagement. Further, it is found that the PLE is positively related to student marks.
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TL;DR: In this article , the authors investigated the relationship between student technology acceptance, student engagement, and perceived learning on tourism-related massive open online courses (MOOCs) and found that technology acceptance has an impact on student engagement but the impact is not highly significant.
Abstract: ABSTRACT This study investigates the relationship between student technology acceptance, student engagement, and perceived learning on tourism-related massive open online courses (MOOCs). The respondents include 389 Indian university students who took tourism-related MOOCs. The results of PLS-SEM indicate the weak relationship between MOOC technology acceptance and the perceived learning of students. Technology acceptance has an impact on student engagement, but the impact is not highly significant. The findings show the strong relationship between student engagement and perceived learning in the context of tourism-MOOCs. The study suggested several ways to ensure student engagement and perceived learning to develop a positive attitude toward MOOC platforms and institutions that deliver MOOCs. Several implications are drawn from the findings, and future research directions are suggested.
11 citations
TL;DR: In this paper , the influence of gamification on sustainable learning in education has been analyzed in the context of the COVID-19 global pandemic in higher education in China, where gamification has been integrated into flipped classrooms to promote learner achievement and engagement.
Abstract: The onset of the COVID-19 global pandemic has negatively impacted sustainable learning in education (SLE). During city lockdowns, higher education institutes (HEIs) have transitioned from adopting solely traditional didactic classroom teaching to including innovative, flexible learning approaches such as flipped classrooms. Gamification is a new techno-pedagogy that has been integrated into flipped classrooms to promote learner achievement and engagement. Grounded in self-determination theory, the objectives of this exploratory study were to analyse the influence of the flipped classroom and gamification on SLE concerning learner achievement and engagement. Participants were recruited from postgraduate business education programmes in China, and three instructional interventions were applied for a semester of 10 weeks. The three instructional interventions applied were: gamified flipped classroom (n = 25), non-gamified flipped classroom (n = 24) and gamified traditional classroom (n = 19). A mixed-methods approach was used, and both quantitative and qualitative data were analysed. The results indicated gamified traditional classrooms promote learner achievement, and the gamified flipped classrooms promote learner engagement. Furthermore, learning culture, such as teacher-dependency, also influence learner achievement and engagement. The class observation reports and learner interviews suggested that both gamified flipped classrooms and gamified traditional classrooms support SLE in the time of academic uncertainty during the COVID-19 pandemic.
11 citations
TL;DR: In this paper, the authors examined how technology overload strains the ability of online learning to meet students' basic psychological needs (BPNs), which can decrease positive outcomes such as academic enjoyment and personal performance.
Abstract: PurposeMost students are considered digital natives and are presumably equipped to handle extensive technology use. However, online learning turns students into involuntary telecommuters when it is the primary modality. The prevailing trends of online learning, digital socialization, telehealth and other online services, combined with remote work has increased students' reliance on information and communications technologies (ICTs) for all purposes, which may be overwhelming. We examine how technology overload strains the ability of online learning to meet students' basic psychological needs (BPNs), which can decrease positive outcomes such as academic enjoyment and personal performance.Design/methodology/approachData was collected via an online survey of 542 university students and the proposed model was tested using partial least squares (PLS) regression.FindingsWe find that technology overload can diminish the positive relationship between online learning intensity and BPNs satisfaction, which is alarming because BPNs satisfaction is critical to students' positive experiences. Moreover, we find that technology overload and lack of technology experience can directly drive BPNs frustration, which decreases positive outcomes and increases academic anxiety.Originality/valueWe extend a theoretical framework for telecommuting to examine online learning. Additionally, we consider the role of technology overload and experience both as drivers and as moderators of students' BPNs satisfaction and frustration in online learning. Our results provide valuable insights that can inform efforts to rebalance the deployment of ICTs to facilitate online educational experiences.
4 citations
20 Sep 2021
TL;DR: In this paper, the effect of various factors, i.e., compatibility, resource availability, subjective norms, subject interest, institutional branding and self-efficacy on students' adoption intention to TEL enrolled in different government and private educational institutes in Chhattisgarh state, was investigated.
Abstract: Technology-enhanced learning (TEL), undoubtedly, creates a big difference in higher education students' knowledge and growth, which helps them become globally competitive in the job market eventually. The present study aims to investigate the effect of various factors, i.e. informational quality, compatibility, resource availability, subjective norms, subject interest, institutional branding and self-efficacy on students' adoption intention to TEL enrolled in different government and private educational institutes in Chhattisgarh state.,The primary data were collected from 600 students from different universities and colleges using purposive sampling technique with “criterion sampling”. Hierarchal multiple regression (stepwise) analysis was used on the collected data.,Results concluded that factors, i.e. compatibility, resource availability, subjective norms, subject interest and institutional branding are significantly and positively influencing students' adoption intention to TEL in Chhattisgarh, whereas self-efficacy and informational quality of TEL did not contribute significant effect for students' adoption intention.,There is a lack of research in the knowledge domain, especially in the field of TEL, in the state of Chhattisgarh. The different variables taken in the present study, such as informational quality, self-efficacy, institutional branding, subjective norms, resource availability, compatibility and subject interest of TEL, are the first of its kind where these variables are being examined on the students' adoption intention to TEL.
3 citations
TL;DR: In this article , the authors explored the mechanisms by which suppression affected MOOC learning and found that suppression was indirectly rather than directly related to the outcomes of MOOC learners' learning through different patterns of mediation.
Abstract: Suppression emotion-regulation tendency was integrated with control-value theory variables (control appraisal, value appraisal, boredom) and behavioral avoidance and MOOC learning outcomes to comprehensively explore the mechanisms by which suppression affected MOOC learning. A total of 191 Chinese university students participated in this study. They completed a pre-test prior to learning a MOOC, and a questionnaire and a post-test at the end of 15-week MOOC. Results of mediation analysis showed that suppression was indirectly rather than directly related to the outcomes of MOOC learning through different patterns of mediation. The pathways found to be significant were through control appraisal, through boredom, and through any two or all of control, boredom, and behavioral avoidance in serial combinations. Value appraisal was found to negatively moderate the relationship between perceived control and boredom. Based on these results, we adduce practical implications for how to reduce learners’ tendency to use suppression in MOOCs, increase their perceived control and value of MOOC learning, and attenuate the boredom they may experience. This study is intended to contribute to expanding our understanding of MOOC learning as an integrated construct under the interplay of emotional, cognitive and behavioral aspects of learners.
3 citations
References
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TL;DR: This article seeks to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating the many ways in which moderators and mediators differ, and delineates the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena.
Abstract: In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.
80,095 citations
TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...
56,555 citations
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
TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.
Abstract: Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
52,531 citations
Book•
27 May 1998TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
Abstract: Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation and pitfalls of structural equation modelling (SEM) in the social sciences. The book covers introductory techniques including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods such as the evaluation of non-linear effects, the analysis of means in convariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the book offers clear instructions on the preparation and screening of data, common mistakes to avoid and widely used software programs (Amos, EQS and LISREL). The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
42,102 citations