Applying the Technology Acceptance Model to Elucidate K-12 Teachers’ Use of Digital Learning Platforms in Thailand during the COVID-19 Pandemic
Abstract
:1. Introduction
The Need for the Study
2. Literature Review and Hypotheses
2.1. Technology Acceptance Model (TAM)
2.2. Technology Self-Efficacy (TSE)
2.3. Subjective Norms (SN)
2.4. Facilitating Conditions (FC)
3. Methodology
3.1. Data and Sample
3.2. Instruments
3.3. Data Analysis
4. Results
4.1. Descriptive Statistics
4.2. Analysis of Measurement Model
4.3. Analysis of the Structural Model
4.4. Testing the Hypotheses
5. Discussion
6. Conclusions
7. Implications for Research
8. 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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List | Numbers |
---|---|
Number of DEEP users (teachers and students) | 627,297 |
Teachers under the Ministry of Education | 549,868 |
Students in schools under the Ministry of Education | 4,293,998 |
Total number of teachers and students | 4,843,866 |
Percentage of DEEP users | 12.95% |
Construct | Items | Sample Items |
---|---|---|
PU | 5 | I think using a DLP enhances my online teaching effectiveness. |
PEU | 4 | A DLP is easy to use. |
ATT | 4 | I enjoy using DLP. |
BI | 4 | I am sure I will use a DLP in the future. |
TSE | 3 | I can solve problems that arise on a DLP by myself. |
SN | 4 | My colleagues think that I should use a DLP. |
FC | 4 | When I encounter difficulties in using a DLP, specialized instruction is available to me. |
Construct | Mean | SD |
---|---|---|
PU | 4.652 | 1.112 |
PEU | 4.514 | 0.812 |
ATT | 4.486 | 0.951 |
BI | 4.619 | 1.107 |
TSE | 4.490 | 1.210 |
SN | 4.369 | 1.170 |
FC | 4.473 | 1.206 |
Construct | Items | Loadings | α | CR | AVE |
---|---|---|---|---|---|
PU | PU1 | 0.859 | 0.930 | 0.901 | 0.645 |
PU2 | 0.850 | ||||
PU3 | 0.780 | ||||
PU4 | 0.782 | ||||
PU5 | 0.739 | ||||
PEU | PEU6 | 0.883 | 0.835 | 0.851 | 0.597 |
PEU7 | 0.922 | ||||
PEU8 | 0.604 | ||||
PEU9 | 0.627 | ||||
ATT | ATT10 | 0.737 | 0.816 | 0.860 | 0.613 |
ATT11 | 0.576 | ||||
ATT12 | 0.946 | ||||
ATT13 | 0.827 | ||||
BI | BI14 | 0.775 | 0.912 | 0.901 | 0.696 |
BI15 | 0.915 | ||||
BI16 | 0.828 | ||||
BI17 | 0.812 | ||||
TSE | TSE18 | 0.765 | 0.904 | 0.734 | 0.892 |
TSE19 | 0.945 | ||||
TSE20 | 0.851 | ||||
SN | SN21 | 0.899 | 0.929 | 0.889 | 0.670 |
SN22 | 0.915 | ||||
SN23 | 0.753 | ||||
SN24 | 0.684 | ||||
FC | FC25 | 0.713 | 0.914 | 0.864 | 0.616 |
FC26 | 0.730 | ||||
FC27 | 0.838 | ||||
FC28 | 0.848 |
PU | PEU | ATT | BI | TSE | SN | FC | |
---|---|---|---|---|---|---|---|
PU | 0.803 | ||||||
PEU | 0.661 | 0.773 | |||||
ATT | 0.692 | 0.621 | 0.783 | ||||
BI | 0.689 | 0.604 | 0.739 | 0.818 | |||
TSE | 0.559 | 0.558 | 0.546 | 0.665 | 0.944 | ||
SN | 0.596 | 0.482 | 0.583 | 0.731 | 0.647 | 0.819 | |
FC | 0.487 | 0.392 | 0.386 | 0.512 | 0.499 | 0.520 | 0.785 |
Fit Indexes | Level of Acceptance Fit | Model | Results |
---|---|---|---|
χ2—test | Non-significant | χ2 = 197.707, df = 253, p = 0.996 | Pass |
χ2/df | <2.00 | 0.781 | Pass |
CFI | ≥0.95 | 1.000 | Pass |
GFI | ≥0.95 | 0.969 | Pass |
AGFI | ≥0.95 | 0.950 | Pass |
NFI | ≥0.95 | 0.994 | Pass |
SRMR | <0.05 (good fit) <0.08 (fair fit) | 0.011 | Pass |
RMSEA | <0.05 | 0.000 | Pass |
Hypotheses | Relationships | Direction | Path Coefficient | t-Value | Results |
---|---|---|---|---|---|
H1 | PU → ATT | Positive | 0.590 | 5.216 *** | Supported |
H2 | PU → BI | Positive | −0.277 | −1.754 | Not supported |
H3 | PEU → PU | Positive | 0.660 | 9.544 *** | Supported |
H4 | PEU → ATT | Positive | 0.355 | 3.183 ** | Supported |
H5 | ATT → BI | Positive | 0.834 | 5.422 *** | Supported |
H6 | TSE → PEU | Positive | 0.409 | 5.368 *** | Supported |
H7 | SN → PU | Positive | 0.30 | 4.956 *** | Supported |
H8 | SN → PEU | Positive | 0.286 | 3.544 *** | Supported |
H9 | SN → BI | Positive | 0.476 | 6.942 *** | Supported |
H10 | FC →PEU | Positive | 0.170 | 2.833 ** | Supported |
H11 | FC → BI | Positive | 0.010 | 0.217 | Not supported |
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Songkram, N.; Osuwan, H. Applying the Technology Acceptance Model to Elucidate K-12 Teachers’ Use of Digital Learning Platforms in Thailand during the COVID-19 Pandemic. Sustainability 2022, 14, 6027. https://doi.org/10.3390/su14106027
Songkram N, Osuwan H. Applying the Technology Acceptance Model to Elucidate K-12 Teachers’ Use of Digital Learning Platforms in Thailand during the COVID-19 Pandemic. Sustainability. 2022; 14(10):6027. https://doi.org/10.3390/su14106027
Chicago/Turabian StyleSongkram, Noawanit, and Hathaiphat Osuwan. 2022. "Applying the Technology Acceptance Model to Elucidate K-12 Teachers’ Use of Digital Learning Platforms in Thailand during the COVID-19 Pandemic" Sustainability 14, no. 10: 6027. https://doi.org/10.3390/su14106027
APA StyleSongkram, N., & Osuwan, H. (2022). Applying the Technology Acceptance Model to Elucidate K-12 Teachers’ Use of Digital Learning Platforms in Thailand during the COVID-19 Pandemic. Sustainability, 14(10), 6027. https://doi.org/10.3390/su14106027