Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic
Abstract
:1. Introduction
2. Literature Review
2.1. Technology Acceptance Model
2.2. Family Support (FS)
2.3. Instructor Attitude
2.4. Task–Technology Fit
3. Research Model and Hypotheses
3.1. Research Model
3.2. Hypotheses
3.3. Construct Operationalization
3.4. Data Collection
4. Results
4.1. Measurement Model
4.2. Structural Model
5. Discussion and Conclusions
5.1. Discussion
5.2. Practical Implications
5.3. Limitations and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Authors | Research Contexts | Constructs | Fundamental Theories |
---|---|---|---|
Baby & Kannammal [22] | e-learning | Perceived Usefulness, Perceived Ease of Use, Perceived Trust, Perceived Security, Perceived Privacy, Information Quality | TAM |
Ayele & Birhanie [23] | e-learning | Training, top management support, incentive | TAM |
Ashrafi et al., [14] | Learning management system | Subjective norm, enjoyment, confirmation, satisfaction, content quality, navigation, presentation | ECT + TAM |
Chang, Hajiyev, & Su [24] | e-learning | Self-efficacy, subjective norm, enjoyment, computer anxiety, technological innovation, experience | ECT + IS success model + continuance theory |
Francis B. Osang et al. [25] | e-learning | systems in terms of attitude towards use, IT usage, user satisfaction and performance | TAM + TRA + IS |
Scherer, Siddiq, & Tondeur [26] | e-learning | Facilitating conditions, subjective norms, technology self-efficacy | TAM |
Weng, Tsai, & Weng [27] | e-learning | e-learning self-efficacy, managerial support, peer support, family support | TAM + social support theory |
Wu & Chen [28] | MOOCs | Individual–technology fit, task–technology fit, openness, reputation, social influence, social recognition | TAM + TTF |
Vanduhe, Nat, & Hasan [29] | Gamification for training in higher education | Social influence, task–technology fit, social recognition | TAM + TTF |
Pozón-López et al. [30] | MOOCs | Vividness of content, interactivity, controlled motivation, autonomous motivation, entertainment, course quality, emotions, satisfaction | TAM |
Lee [31] | e-learning | Confirmation, satisfaction, enjoyment, concentration, subjective norm, behavior control | ECT + TAM + TPB + Flow theory |
Zhonggen & Xiaozhi [32] | Mobile learning | Peer influence, superior influence, enjoyment, subjective norm, image, job relevance, output quality, result demonstrability, adjustment, experience, anchor, voluntariness | TAM2 |
Al-Rahmi et al. [33] | MOOCs | Compatibility, trainability, complexity, observability, relative advantage | TAM + IDT |
Sun & Gao [34] | Mobile learning | Intrinsic motivation, task–technology fit | TAM + TTF + intrinsic motivation |
Cheng [35] | e-learning | Subjective norm, behavior control, self-esteem | TAM + TPB |
Romero-Frías et al. [36] | MOOCs | Loyalty, external regulation, intrinsic motivation | TAM + self-determination theory |
Construct | Factor Loading | α | CR | AVE | VIF |
---|---|---|---|---|---|
Perceived usefulness | 0.943 *** 0.949 *** | 0.882 | 0.943 | 0.895 | 2.337 |
Perceived ease of use | 0.894 *** 0.924 *** 0.941 *** | 0.909 | 0.944 | 0.846 | 1.722 |
Attitude | 0.913 *** 0.898 *** 0.885 *** | 0.881 | 0.926 | 0.808 | 1.552 |
Continuance intention | 0.956 *** 0.958 *** 0.947 *** | 0.950 | 0.927 | 0.909 | DV |
Instructor attitude | 0.875 *** 0.908 *** 0.912 *** | 0.882 | 0.968 | 0.807 | 2.249 |
Family support | 0.903 *** 0.908 *** 0.892 *** 0.850 *** | 0.911 | 0.937 | 0.789 | 2.253 |
Task–technology fit | 0.914 *** 0.938 *** 0.914 *** 0.854 *** | 0.926 | 0.948 | 0.820 | 1.945 |
AT | CIT | PEU | PU | TTF | FS | IAT | |
---|---|---|---|---|---|---|---|
AT | 0.899 | ||||||
CIT | 0.723 | 0.954 | |||||
PEU | 0.639 | 0.520 | 0.920 | ||||
PU | 0.756 | 0.674 | 0.596 | 0.946 | |||
TTF | 0.807 | 0.668 | 0.621 | 0.758 | 0.905 | ||
FS | 0.653 | 0.496 | 0.609 | 0.538 | 0.593 | 0.888 | |
IAT | 0.657 | 0.376 | 0.603 | 0.513 | 0.598 | 0.693 | 0.899 |
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Mo, C.-Y.; Hsieh, T.-H.; Lin, C.-L.; Jin, Y.Q.; Su, Y.-S. Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic. Sustainability 2021, 13, 5471. https://doi.org/10.3390/su13105471
Mo C-Y, Hsieh T-H, Lin C-L, Jin YQ, Su Y-S. Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic. Sustainability. 2021; 13(10):5471. https://doi.org/10.3390/su13105471
Chicago/Turabian StyleMo, Chuan-Yu, Te-Hsin Hsieh, Chien-Liang Lin, Yuan Qin Jin, and Yu-Sheng Su. 2021. "Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic" Sustainability 13, no. 10: 5471. https://doi.org/10.3390/su13105471