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, however, 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 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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".