Viability of the “Technology Acceptance Model” in Multimedia Learning Environments: A Comparative Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In recent years, more and more higher education institutions have interests of integrating internet-based technologies in the classroom as part of the learning environment. Compared to studies on other information technologies, users’ behavior towards this type of systems, however, has not been assessed and understood thoroughly. In order to get more experience about human behaviors on multimedia learning environment, we conducted a comparative study consisting of 362 students, which is almost three times the sample size of the previous study, participating to test the theoretical model. Results suggest that TAM is a solid theoretical model where its validity can extend to the multimedia and e-learning context. The study provides a more intensive view of the multimedia learning system users and is an important step towards a better understanding of the user behavior on the system and a multimedia acceptance model.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it