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研究生:李宗文
研究生(外文):Theerapong Binali
論文名稱:大學生線上學習樣貌、網路知識觀、後設認知調整以及線上學習投入之研究
論文名稱(外文):University students’ online learning profiles, internet-specific epistemic beliefs, metacognitive regulation and engagement in online learning
指導教授:黃國禎黃國禎引用關係
指導教授(外文):Gwo-Jen Hwang
口試委員:張欣怡蔡今中至中​梁蔡孟蓉
口試委員(外文):Hsin-Yi ChangChin-Chung TsaiJyh-Chong LiangMeng-Jung Tsai
口試日期:2021-06-25
學位類別:博士
校院名稱:國立臺灣科技大學
系所名稱:數位學習與教育研究所
學門:教育學門
學類:教育科技學類
論文種類:學術論文
論文出版年:2021
畢業學年度:109
語文別:英文
論文頁數:125
中文關鍵詞:online learning profilesmetacognitive regulationinternet-specific epistemic beliefstudent engagementPLS-SEM
外文關鍵詞:online learning profilesmetacognitive regulationinternet-specific epistemic beliefstudent engagementPLS-SEM
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The overall purpose of this research was to investigate the relationships among university students’ online learning profiles, internet-specific epistemic beliefs, metacognitive regulation, and engagement in online learning. This research incorporated two studies, namely Studies I and Study II, that aligned with the overall purpose. The purpose of Study I was to investigate the differences in online learning purposes and engagement among university students by analyzing their online learning profiles. Moreover, Study I examined how students with different online learning profiles would exhibit differences in terms of their online learning activities, online metacognitive regulation and internet-specific epistemic justification (ISEJ). In Study II, the research focused on engagement as a variable in online learning profiles. This investigation aligned with literature review and Study I findings that demonstrated how engagement plays a crucial role in online learning. In this sense, the purpose of Study II was to adopt a partial least squares-structural equation modeling approach (PLS-SEM) to investigate the structural relationships among internet-based epistemic justification, online metacognitive regulation, and engagement in online learning among university students. The analysis was divided into two parts: an investigation into the structural relationships using the whole group sample and a multi-group analysis to identify the structural relationships using different groups within the sample classified by their internet-specific epistemic beliefs.

In Study I, 389 participants who were undergraduate and graduate students in Thailand responded to three questionnaires. After conducting further analysis on the collected data, the participants were classified into four categories, including highly engaged, course-driven online learners (Cluster 1), less engaged, self-driven online learners (Cluster 2), less engaged, course-driven online learners (Cluster 3), and highly engaged, self-driven online learners (Cluster 4). Participants from the four clusters had different online learning profiles and depicted disparities in their online learning activities, online metacognitive regulation and internet-specific epistemic beliefs.

In Study II, the participants consisted of 300 Thai undergraduate students. Similar to Study I, Study II employed a questionnaire survey as the primary data collection instrument. The measurement model indicated that all constructs from the three adapted research instruments established sufficient reliability and validity, thereby justifying their subsequent use in PLS-SEM analyses. The results of structural relationships among the latent variables showed that all the three ISEJ constructs, including personal justification, justification by multiple sources, and justification by authority were positive predictors of metacognitive regulation in online learning whereas this construct further positively predicted all four aspects on engagement in online learning, including, behavioral, cognitive, social, and emotional engagement.

Moreover, the multi-group analysis further revealed that, for students possessing more sophisticated internet-specific epistemic beliefs (Group1), all the three ISEJ aspects including personal justification, justification by multiple sources, and justification by authority were significant positive predictor of online metacognitive regulation. For students possessing less sophisticated internet-specific epistemic beliefs (Group 2), personal justification was the only significant positive predictor of online metacognitive regulation. Nevertheless, it was found that online metacognitive regulation was significant positive predictors of all aspects of engagement in online learning (behavioral, cognitive, social, and emotional engagement) across the two groups. Discussion and implications were made based on the lessons learned in both Study I and Study II
The overall purpose of this research was to investigate the relationships among university students’ online learning profiles, internet-specific epistemic beliefs, metacognitive regulation, and engagement in online learning. This research incorporated two studies, namely Studies I and Study II, that aligned with the overall purpose. The purpose of Study I was to investigate the differences in online learning purposes and engagement among university students by analyzing their online learning profiles. Moreover, Study I examined how students with different online learning profiles would exhibit differences in terms of their online learning activities, online metacognitive regulation and internet-specific epistemic justification (ISEJ). In Study II, the research focused on engagement as a variable in online learning profiles. This investigation aligned with literature review and Study I findings that demonstrated how engagement plays a crucial role in online learning. In this sense, the purpose of Study II was to adopt a partial least squares-structural equation modeling approach (PLS-SEM) to investigate the structural relationships among internet-based epistemic justification, online metacognitive regulation, and engagement in online learning among university students. The analysis was divided into two parts: an investigation into the structural relationships using the whole group sample and a multi-group analysis to identify the structural relationships using different groups within the sample classified by their internet-specific epistemic beliefs.

In Study I, 389 participants who were undergraduate and graduate students in Thailand responded to three questionnaires. After conducting further analysis on the collected data, the participants were classified into four categories, including highly engaged, course-driven online learners (Cluster 1), less engaged, self-driven online learners (Cluster 2), less engaged, course-driven online learners (Cluster 3), and highly engaged, self-driven online learners (Cluster 4). Participants from the four clusters had different online learning profiles and depicted disparities in their online learning activities, online metacognitive regulation and internet-specific epistemic beliefs.

In Study II, the participants consisted of 300 Thai undergraduate students. Similar to Study I, Study II employed a questionnaire survey as the primary data collection instrument. The measurement model indicated that all constructs from the three adapted research instruments established sufficient reliability and validity, thereby justifying their subsequent use in PLS-SEM analyses. The results of structural relationships among the latent variables showed that all the three ISEJ constructs, including personal justification, justification by multiple sources, and justification by authority were positive predictors of metacognitive regulation in online learning whereas this construct further positively predicted all four aspects on engagement in online learning, including, behavioral, cognitive, social, and emotional engagement.

Moreover, the multi-group analysis further revealed that, for students possessing more sophisticated internet-specific epistemic beliefs (Group1), all the three ISEJ aspects including personal justification, justification by multiple sources, and justification by authority were significant positive predictor of online metacognitive regulation. For students possessing less sophisticated internet-specific epistemic beliefs (Group 2), personal justification was the only significant positive predictor of online metacognitive regulation. Nevertheless, it was found that online metacognitive regulation was significant positive predictors of all aspects of engagement in online learning (behavioral, cognitive, social, and emotional engagement) across the two groups. Discussion and implications were made based on the lessons learned in both Study I and Study II
TABLE OF CONTENTS

ABSTRACT i
ACKNOWLEDGEMENTS iii
TABLE OF CONTENTS v
LIST OF TABLES vii
LIST OF FIGURES viii

CHAPTER ONE INTRODUCTION 1
Research Background 1
Research Purposes and Research Questions 3
Terms and Definitions 4

CHAPTER TWO LITERATURE REVIEW 7
Online Learning Profiles 7
Online Learning Purposes 7
Online Learning Engagement 8
Online Learning Activity 11
Metacognition 12
Conceptualization of Metacognition 12
Components of Metacognition 13
Metacognitive Regulation in Online Learning 14
Recent Perspectives on Metacognitive Regulation 15
Epistemic beliefs 17
Theoretical Perspectives Regarding Epistemic Beliefs 17
Notions of Epistemic Justification 18
Internet-Specific Epistemic Justification and Its Multidimensionality 19
Characteristics of Students Holding Different Epistemic Justification Beliefs 20
Research Hypotheses 21

CHAPTER THREE METHODOLOGY 23
General Research Design 23
Study I: Participants' Demographic Profile 24
Instruments 25
Types and Purposes of Online Learning 25
Online Learning Engagement Questionnaire 26
Metacognitive Regulation of Online Learning Questionnaire26
Internet-Specific Epistemic Justification (ISEJ) 27
Procedures of Data Collection 28
Data Analysis 29
Study II: Participants' Demographic Profile 30
Instruments 30
Procedures of Data Collection 31
Data Analysis 31
The Measurement Model 32
The Higher-Order Construct 33
The Structural Model 34
The Multi-Group SEM Analysis 35

CHAPTER FOUR RESULTS 37
Study I: Overview of the University Students' Online Learning 37
Characterizing Students' Profiles of Online Learning 39
Exploring Differences in Epistemic Justification and Metacognitive Regulation among Students with Different Online Learning Profiles 42
Summary of the Results 45
Study II: Assessment of the Reliability and Validity of the Measurement Model 48
Structural Relationships among the Latent Variables (Whole Group Sample) 50
Multi-Group Analysis of the Structural Relationships among the Latent Variables 52
Group 1 (Students with More Sophiticated Internet-soecific Epistemic Beliefs) 56
Group 1I (Students with Less Sophiticated Internet-soecific Epistemic Belief) 57
Summary of the Results 61

CHAPTER FIVE DISCUSSION AND CONCLUSION 64
Overview of the University Students’ Online Learning Profiles 64
Relations between Students’ Online Learning Profiles and Online Learning Activities 66
Relations between Students’ Online Learning Profiles and their Metacognitive Regulation in Online Learning 67
Relations between Students’ Online Learning Profiles and their Internet-specific Epistemic Beliefs 68
Personal Justification 68
Justification by Multiple Sources 69
Justification by Authority 69
Structural Relations between University Students’ Internet-specific Epistemic Beliefs and their Metacognitive Regulation in Online Learning 70
Personal Justification and Metacognitive Regulation 70
Justification by Multiple Sources and Metacognitive Regulation 71
Justification by Authority and Metacognitive Regulation 72
Structural Relations between University Students’ Metacognitive regulation and their Engagement in Online Learning 73
Metacognitive Regulation and Online Learning Engagement 73
Conclusion 74

REFERENCES 76
APPENDICES 100
APPENDIX 1 Interview Questions 101
APPENDIX 2 Tyypes and Purposes of Online Learning 103
APPENDIX 3 Student Engagement in Online Learning 105
APPENDIX 4 Metacognitive Regulation of Online Learning Questionnaire 108
APPENDIX 5 The Internet-Specific Epistemic Justification (ISEJ) 110
APPENDIX 6 A Screenshot of Study I’s Informed Consent Form 113
APPENDIX 7 A Screenshot of Study II’s Informed Consent Form 114
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1. 大學生線上學習感知、學習行為、學習成就與課程滿意度於線上學習模式與混成學習模式之關係研究─以自我決定理論觀點探討線上學習感知
2. 藉由電子書學習系統探討學生線上學習準備度、線上學習行為與學習成果之間的關係-以微積分課程為例
3. 線上學習者的成就目標以及其對遊戲化線上學習平台中的遊戲因子的態度
4. 基於概念圖的自律學習模式對學生的STEM學習成就和高層次思考能力之影響
5. 以學習分析初探線上學習者之學習動機對其線上學習行為模式之影響:以校園學術研究倫理課程為例
6. 以自我導向學習預測高等教育學生在線上學習環境中的學習自我效能和學習參與: SEM 分析
7. 基於同儕互評的線上學習模式對學生媒體素養及高層次能力的影響
8. 結合概念圖之人工智能聊天機器人方法對EFL學生英語口語表達能力的影響
9. 探討在線上學習系統中學生的學習投入、線上學習行為 與學業成績之間的關係-以微積分課程為例
10. 智慧化回饋對線上學習者之學習自我效能、投入度與線上學習行為之影響:以校園學術研究倫理課程為例
11. 線上學習推廣之研究─以學習者觀點探討線上學習與傳統學習之比較
12. 後疫情時代的線上學習對學習成效的影響:自我效能、線上學習策略
13. 利害關係人管理策略應用於線上學習之研究-以YouTube線上學習使用者為例
14. 基於聊天機器人的虛擬實境學習模式對護理學生輸血安全培訓成效之影響
15. 基於雙層次問題導向學習機制之情境式電腦遊戲對學生園藝課程學習成就及行為之影響