Factors Influencing Digital Transformation Adoption among Higher Education Institutions during Digital Disruption
Why this work is in the frame
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Bibliographic record
Abstract
This research aims to apply confirmatory factor analysis to identify the digital transformation components for higher education institutions. The research sample consisted of 300 personnel from agencies within higher education institutions, which are higher education institutions under the Ministry of Higher Education, Science, Research and Innovation, Thailand that use the database system on educational quality assurance called Commission on Higher Education Quality Assessment online system (CHE QA Online). The selection was the result of multi-stage random sampling from 100 higher education instructions. The research tool was an online questionnaire form on factors influencing the success of information systems in the digital transformation for higher education institutions by 5-level rating scale based on the Likert's scale. The result revealed that digital transformation factor consistent with empirical data (p-value = 0.860), which consist of 6 components: 1) Strategy 2) Process 3) Product/Service 4) People 5) Data) and 6) Technology. The research findings help higher education institutions prepare for the elements necessary for the institutional transformation to a digital organization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| 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