本研究運用「推-拉-繫住力」理論框架，探討學生從傳統課堂學習轉向AI輔助語言學習的轉換行為。研究歸納了了影響此轉換的關鍵因素，包括推力因素（社交孤立、價格、互動不足）、拉力因素（彈性、可及性、個人化學習）及繫住力因素（技術熟練度、自律性）。結果顯示，推力與拉力因素均顯著影響轉換意圖，其中拉力因素的影響力更強。此外，繫住力因素中的技術熟練度與自律性會提升轉換意圖，但未對推力或拉力因素產生調節作用。本研究不僅擴展了PPM理論的應用，也為教育者與人工智慧系統平台業者提供了優化學習的建議。

This study explores students’ switching behaviors between traditional classroom learning and AI tutor-assisted learning using the Push-Pull-Mooring (PPM) framework. The research identifies key factors influencing this transition, including push factors (social isolation, price, interaction), pull factors (flexibility, accessibility, personalization) and mooring factors (technical proficiency, self-discipline). Findings show that both push and pull factors significantly impact switching intention, with pull factors exerting a stronger influence. Additionally, technical proficiency and self-discipline directly enhance switching intention, though they do not moderate the influence of push or pull effects on switching intention. The study offers theoretical contributions to the PPM framework and practical implications for educators and AI platforms to optimize learning effects.

Thesis Validation Letter i
摘要 ii
Abstract iii
TABLE OF CONTENTS iv
LISTS OF FIGURES viii
LIST OF TABLES ix
CHAPTER - 1 INTRODUCTION 1
1.1 Research background and motivation 1
1.2 Research objectives 5
CHAPTER – 2 LITERATURE REVIEW 6
2.1 The importance of education 6
2.2. The importance of language learning 8
2.3 Traditional Learning (A classroom teaching method) 11
2.4 Online Learning (AI Virtual Learning) 14
2.5 Push-Pull-Mooring Framework 18
2.5.1 Push Effect 24
2.5.1.1 Social Isolation (SI) 33
2.5.1.2 Price (PR) 38
2.5.1.3 Interaction (SO) 42
2.5.2 Pull Effect 46
2.5.2.1 Flexibility (FL) 53
2.5.2.2 Accessibility (AC) 56
2.5.2.3 Personalization (PE) 58
2.5.3 Mooring Effect 61
2.5.3.1 Technical Proficiency (TP) 67
2.5.3.2 Self-discipline (SD) 71
2.6 Switching Intention (SW) 77
CHAPTER – 3 RESEARCH METHODOLOGY 82
3.1 Push-Pull-Mooring (PPM) Research Model 82
3.2 Research Hypotheses 83
3.2.1 The relationship between push effect and students’ switching intention 83
3.2.2 The relationship between pull effect and students’ switching intention 86
3.2.3 The relationship between mooring effect and students’ switching intention 88
3.3 Questionnaire Design 92
3.4 Questionnaire Pretest 96
3.5 Data Collection 96
3.6 Data Analysis 97
CHAPTER – 4 RESEARCH RESULTS 98
4.1 Research Introduction 98
4.2 Descriptive Statistical Analysis 98
4.2.1 Demographic Characteristics of the Respondents 98
4.2.2 Behavioral Characteristics of the Respondents 101
4.3 Measurement Model Evaluation 102
4.3.1 Reliability and Convergent Validity 102
4.3.2 Discriminant Validity 106
4.4 Second-Order Formative-Measured Construct Analysis 108
4.5 Structural Equation Analysis (Hypotheses Testing) 109
4.5.1 Hypotheses Testing Results 109
CHAPTER – 5 CONCLUSION 112
5.1 Research Findings 112
5.1.1 The positive relationship between push and switching intention 112
5.1.2 The positive relationship between pull and switching intention 112
5.1.3 The positive relationship between technical proficiency and switching intention 113
5.1.4 The negative relationship between technical proficiency and push factors 113
5.1.5 The negative relationship between technical proficiency and pull factors 114
5.1.6 The positive relationship between self-discipline and switching intention 114
5.1.7 The negative relationship between self-discipline and push factors 115
5.1.8 The negative relationship between self-discipline and pull factors 115
5.2 Theoretical Implications 117
5.3 Managerial Implications 120
5.4 Limitations of the study and future discussions 122
References 123
Appendix 158

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