Asynchronous Electronic Discussion Group: Analysis of Postings and Perception of In-Service Teachers.
Bibliographic record
Abstract
This paper examines the practice of online discussion in a course specially tailored for in-service teachers who are pursuing their basic degree qualification at a teacher training institute. Analyses of postings to the asynchronous electronic discussion group were made according to the type of postings as proposed by Poole (2000). Four focus areas were looked into, that is, content, technical, procedural, or non-academic. Analyses were done for each quarter of the 12 weeks of interaction. At the end of the learners’ participation in the EDG and before their end-of-course examination, the participants were then given a paper-based questionnaire asking their perceptions on the use of EDG as part of their coursework on the whole. Six aspects of EDG were examined, these are; Ø technical aspects, Ø motivation to use the EDG, Ø quality of interaction, Ø tutor’s response, Ø perceived learning, and Ø attitude towards EDG. Analyses on postings for the EDG showed that the bulk of the postings were made in the last quarter of the online discussions. Further, 97.8% of the postings were on content and the types of content posting registered were predominantly questions (41.19%) and those that sought clarification/elaboration (37.48%). Findings from this study suggest that overall the participants were satisfied with the six aspects of EDG examined. The aspect that recorded the highest mean was ‘motivation to read tutor’s responses’ whilst the lowest mean (and the only one with negative perception) was for ‘worthiness of time spent on online discussions’.
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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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".