Investigating Lifelong Learners’ Continuing Learning Intention Moderated by Affective Support in Online Learning
Abstract
:1. Introduction
2. Relative Studies Based on the Theories of TAM and ECM
2.1. Concepts
2.2. The Relationship between Perceived Usefulness and Perceived Ease of Use and Learning Satisfaction
2.3. The Continuing Learning Intentions Relationship between Perceived Usefulness and Perceived Ease of Use
2.4. Relationship between Learning Satisfaction and the Continuing Learning Intention
2.5. Moderating Function for Affective Support
2.6. Hypothesis
3. Materials and Methods
3.1. Settings and Participants
3.2. Questionnaires and Measurement of Variables
3.3. Common Methods Biases Test
4. Results
4.1. The Reliability and Validity Analysis
4.2. Structural Equation Modelling and Path Coefficient Estimation
4.3. Moderation Effects Test
4.4. Moderation Test
5. Discussion
5.1. Perceived Usefulness and Perceived Ease of Use Interaction with Learning Satisfaction
5.2. Interaction between Perceived Usefulness, Perceived Ease of Use and the Continuing Learning Intention
5.3. Moderation Effect for Affective Support
6. Conclusions
6.1. Limitations and Contributions
6.2. Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Demographics | Groups | Frequency | Percentage (%) | Characteristics | Groups | Frequency | Percentage (%) |
---|---|---|---|---|---|---|---|
Gender | Male | 218 | 44.67 | Location of students sources | Village/Town | 216 | 44.26 |
Female | 270 | 55.33 | Town/City | 175 | 35.86 | ||
Age | 30 and under | 284 | 58.20 | Metropolitan/Major City | 97 | 19.88 | |
31–40 | 153 | 31.40 | Online Learning programmes | Management | 98 | 20.08 | |
41+ | 51 | 10.40 | Education | 143 | 29.30 | ||
Prior learning background | Subjects The same subjects | 124 | 25.41 | Science and Technology | 147 | 30.12 | |
Similar subjects | 139 | 28.49 | Finance | 39 | 8.00 | ||
New subjects | 225 | 46.10 | Other Programs | 61 | 12.50 |
Dimension | Item | Non-Standardized Coefficient | Standard Error | t-Value | p Value | Standardization Coefficient | Cronbach’ α | CR | AVE |
---|---|---|---|---|---|---|---|---|---|
PEoU | EU1 | 1.000 | 0.934 | 0.956 | 0.955 | 0.811 | |||
EU2 | 1.043 | 0.026 | 40.722 | <0.001 | 0.945 | ||||
EU3 | 1.039 | 0.032 | 32.738 | <0.001 | 0.884 | ||||
EU4 | 0.930 | 0.028 | 33.127 | <0.001 | 0.887 | ||||
EU5 | 0.919 | 0.031 | 29.419 | <0.001 | 0.850 | ||||
PU | UF1 | 1.000 | 0.886 | 0.972 | 0.972 | 0.853 | |||
UF2 | 1.047 | 0.035 | 30.311 | <0.001 | 0.898 | ||||
UF3 | 1.062 | 0.033 | 32.275 | <0.001 | 0.921 | ||||
UF4 | 1.096 | 0.033 | 33.256 | <0.001 | 0.932 | ||||
UF5 | 1.139 | 0.033 | 34.392 | <0.001 | 0.943 | ||||
UF6 | 1.107 | 0.031 | 35.914 | <0.001 | 0.958 | ||||
LS | SAT1 | 1.000 | 0.967 | 0.986 | 0.986 | 0.947 | |||
SAT2 | 1.023 | 0.017 | 59.848 | <0.001 | 0.970 | ||||
SAT3 | 1.023 | 0.016 | 64.874 | <0.001 | 0.980 | ||||
SAT4 | 1.008 | 0.016 | 63.092 | <0.001 | 0.976 | ||||
CLI | BH1 | 1.000 | 0.946 | 0.957 | 0.957 | 0.882 | |||
BH2 | 1.015 | 0.025 | 40.836 | <0.001 | 0.937 | ||||
BH3 | 1.055 | 0.026 | 40.292 | <0.001 | 0.934 | ||||
AS | EM1 | 1.000 | 0.877 | 0.946 | 0.947 | 0.857 | |||
EM2 | 1.073 | 0.033 | 32.717 | <0.001 | 0.949 | ||||
EM3 | 1.113 | 0.034 | 32.687 | <0.001 | 0.949 |
Hypothesis | Path Relationship | Unstd. | S.E. | Z- | Sig. | Std. | Support |
---|---|---|---|---|---|---|---|
H1 | PeoU → LS | 0.104 | 0.037 | 2.798 | 0.005 | 0.101 | yes |
H2 | PU → LS | 0.698 | 0.043 | 16.178 | <0.001 | 0.637 | yes |
H3 | PeoU → CLI | 0.203 | 0.025 | 8.269 | <0.001 | 0.288 | yes |
H4 | PU → CLI | 0.240 | 0.034 | 7.025 | <0.001 | 0.319 | yes |
H5 | LS → CLI | 0.272 | 0.031 | 8.762 | <0.001 | 0.396 | yes |
Effect Category | Effect Size | Coefficient Derived Value | Bootstrapping | Relative Effect Percentage | ||
---|---|---|---|---|---|---|
Bias-Corrected 95% CI | ||||||
SE | Z-Value | LLCI | ULCI | |||
Direct effectiveness | 0.443 | 0.110 | 4.027 | 0.223 | 0.645 | 67.02% |
Total indirect effectiveness | 0.218 | 0.083 | 2.627 | 0.104 | 0.443 | 32.98% |
Total effectiveness | 0.661 | 0.071 | 9.310 | 0.516 | 0.793 | 100% |
Specific indirect effects | ||||||
EU → SAT → BH | 0.028 | 0.015 | 1.867 | 0.019 | 0.117 | 4.24% |
UF → SAT → BH | 0.190 | 0.085 | 2.235 | 0.076 | 0.417 | 28.74% |
Comparison of mediation effects | ||||||
EU → SAT → BH vs. UF → SAT → BH | 0.161 | 0.099 | 1.626 | 0.030 | 0.412 |
Dependent Variable | Independent Variable | Unstd. | SE | t | p | LLCI | ULCI |
---|---|---|---|---|---|---|---|
BH | Constant | 4.674 | 0.017 | 270.656 | 0.000 | 4.64 | 4.707 |
EU | 0.373 | 0.054 | 6.918 | 0.000 | 0.267 | 0.479 | |
EM | 0.386 | 0.055 | 7.071 | 0.000 | 0.279 | 0.493 | |
EM * EU | 0.083 | 0.022 | 3.744 | 0.000 | 0.039 | 0.127 | |
R² = 0.563, F = 207.573, p < 0.001; ΔR² = 0.013, ΔF = 14.016, p < 0.001 | |||||||
BH | Constant | 4.665 | 0.018 | 266.452 | 0.000 | 4.631 | 4.699 |
UF | 0.455 | 0.073 | 6.27 | 0.000 | 0.313 | 0.598 | |
EM | 0.320 | 0.074 | 4.309 | 0.000 | 0.174 | 0.466 | |
EM * UF | 0.100 | 0.022 | 4.554 | 0.000 | 0.057 | 0.143 | |
R² = 0.562, F = 207.348, p < 0.001; ΔR² = 0.019, ΔF = 20.738, p < 0.001 |
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Tang, W.; Zhang, X.; Tian, Y. Investigating Lifelong Learners’ Continuing Learning Intention Moderated by Affective Support in Online Learning. Sustainability 2023, 15, 1901. https://doi.org/10.3390/su15031901
Tang W, Zhang X, Tian Y. Investigating Lifelong Learners’ Continuing Learning Intention Moderated by Affective Support in Online Learning. Sustainability. 2023; 15(3):1901. https://doi.org/10.3390/su15031901
Chicago/Turabian StyleTang, Wen, Xiangyang Zhang, and Youyi Tian. 2023. "Investigating Lifelong Learners’ Continuing Learning Intention Moderated by Affective Support in Online Learning" Sustainability 15, no. 3: 1901. https://doi.org/10.3390/su15031901