A Study of Online English Language Teacher Education Programmes in Distance Education Context in Pakistan
Bibliographic record
Abstract
Technology-based initiatives have transformed the process of teaching and learning activities at formal institutions generally and distance education institutions particularly. Distance education is at the heart of the digital age making maximum use of the emerging technologies. Researchers have favoured computer mediated communications (CMC) for improving the quality of teacher education in developing countries by providing access to more and better educational resources. The researchers designed a CMC-ELT blended model and offered online English language teacher education courses at post-graduate level. A group of students enrolled in MA TEFL programme of Allama Iqbal Open University (AIOU) Islamabad Pakistan, was selected randomly and was guided through CMC-ELT blended model. The results of the study showed that the online support in distance education enhanced students’ performance in terms of access, interaction and cost. The effective use of online support in distance education can improve the quality of English language teaching programmes in Pakistan.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".