Test of e-Learning Related Attitudes (TeLRA) scale: development, reliability and validity study
Bibliographic record
Abstract
The Tanzanian education system is in transition from face -to-face classroom learning to e-learning. E-learning is a new learning approach in Tanzanian Higher Learning Institutions [HLIs] and with teachers being the key stakeholders of all formal education, investigating their attitude towards e-learning is essential. So far, how ever, there has been little consideration given to research that examines teachers’ attitudes towards e-learning in Tanzanian HLIs and consequently, there is no standard attitude scale that has been developed to measure this. This paper presents the development and validation of a scale of teachers’ attitude to e-learning. Whilst being initially developed to assess the attitude of teachers in HLIs the authors belief, having piloted with pre-service trainee teachers in England that the scale transfers across national boundaries. The final instrument contains 36 items with a Cronbach alpha score of 0.857. Although the developed attitude scale was intended for use in HLIs, it can also be of interest to researchers investigating attitudes on other sectors.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".