Integration of the High-tech and Low-tech in Distance Teacher Training in China: An insight from the case of Jiangsu Radio and Television University
Bibliographic record
Abstract
This paper reports the result and subsequent exploration of the pilot multi-media in-service teacher training programme with BA degree (non-honour) ( English Language Education) undertaken in the past three years (2001-2004) in China’s distance education. Through the integration of low-tech and high-tech in instructing and delivering courses, many interesting findings have been unexpectedly obtained. Both the trainers (the university lectures) and trainees (in-service school teachers) have experienced a great transformation in their language teaching and learning: a). the trainees (in-service school teachers) have become more independent learners since they raised their educational level; b). the trainers (university lecturers) have learned to adjust their roles in classroom teaching: to be more learner-centred and less teacher-centred; c). acommunicative task-based approach has been satisfactorily adopted and implanted into the process of learning and teaching; d). the trainees have not only upgraded their qualifications but also their teaching methodology. Based on the findings from the case, the authors offer suggestions for the future development of distance teacher training.
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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 | 0.006 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".