Factors affecting the adoption of blended learning strategy
Bibliographic record
Abstract
The aim of this study is to explore factors affecting the adoption of blended learning strategy. Data was collected using a questionnaire consisting of 42 items, distributed to a random sample of 174 faculty members of Saudi Electronic University and Qassim University. IBM SPSS was used to conduct data analysis. Supporting research hypothesis indicates that student, institutional and learning variables had significant influences on the adoption of blended learning strategy. Considering the findings, it was concluded that the adoption of a blended learning strategy depends not only on the technological aspect of the learning process but also on people, i.e., students who are engaged in the process and motivated teachers who possess the required knowledge and skills. The most important implication of this research is that policy and decision makers in business educational schools are requested to consider factors that had a significant effect on the adoption of blended learning. In doing that, the research contributes to the blended learning knowledge via highlighting the key variables that encourage or hinder the adoption of blended learning strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.034 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".