Adoption of a Social Learning Platform in Higher Education: An Extended UTAUT Model Implementation
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this research is to investigate the factors influencing the adoption of a social learning platform called PairForm using an extended unified theory of acceptance and use of technology (UTAUT) model. The UTAUT extension consists of adding three personal characteristics of students, namely autonomy, anxiety, and attitude. Data obtained from 85 Frenchspeaking students and 14 English-speaking students at the Skema Business School, a higher education institution, showed good reliability coefficients and satisfactory convergent and discriminant validities. Regression analysis suggests the facilitating conditions construct is the main predictor of behavioral intention to use and behavioral use of PairForm. Attitude is the only personal characteristic that explains behavioral intention to use. In the light of these results, we propose recommendations that, if implemented, could create more favorable conditions for the use of social learning technologies.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.009 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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