The influence of collective asynchronous discourse elaborated online by pre-service teachers on their educational intervention in the classroom
Bibliographic record
Abstract
Networked learning communities are growing and they offer new opportunities for reflection on practice in education. Many authors have studied the processes followed and the contents produced by such communities. On the other hand, few have observed how collective asynchronous discourse can be enacted in the classroom. This objective was pursued in the context of this exploratory research. Data was provided by asynchronous discourse written on the Knowledge Forum by five pre-service teachers during a 14-week practicum throughout the winter 2011 semester, as well as in situ observations from their university supervisor, while they were teaching students. Qualitative and descriptive quantitative analyses were conducted. In particular, results showed participants were highly concerned with quality of teaching when elaborating collectively in the electronic forum regarding ideas of interventions, and with the importance of properly handling the possible enactment of such ideas in the classroom while teaching. \n \nLes communautés d’apprentissage en réseau se multiplient et elles offrent de nouvelles avenues pour réfléchir aux pratiques en éducation. De nombreux auteurs étudient les processus utilisés et les contenus produits par ces communautés. Par contre, peu se sont penchés sur l’utilisation de discours collectifs asynchrones dans une classe. C’est l’objectif poursuivi dans cette recherche exploratoire. Les données provenaient de propos asynchrones rédigés sur le Knowledge Forum par cinq futurs enseignants au cours d’un stage de 14 semaines durant le semestre de l’hiver 2011 ainsi que d’observations in situ de leur superviseur universitaire. Des analyses quantitatives descriptives et qualitatives ont été effectuées. Les résultats ont montré notamment que les participants au forum électronique se préoccupaient au plus haut point, lors de leurs échanges sur des interventions possibles, de la qualité de l’enseignement et de l’importance de mettre en oeuvre, le cas échéant, ces idées en classe de façon adéquate.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".