Teachers’ roles in designing meaningful tasks for mediating language learning through the use of ICT: A reflection on authentic learning for young ELLs / Le rôle des enseignants dans la conception de tâches pertinentes en apprentissage des langues
Bibliographic record
Abstract
Task based learning (TBL) continues to evolve as information and communication technology (ICT) inspired tools and teaching approaches afford the possibilities of transforming students’ learning experiences by heightening their motivation and sense of autonomy, and in turn, their vocabulary development. To capture this synergy, teachers will need to reimagine authentic learning and task design. This paper describes and reflects on the shifting demands and roles of the teacher in the elementary school setting. An illustrative sample of a series of linked tasks provides a model for pre-service teachers as they take on the work of preparing meaningful work for ELLs who are increasingly present in today’s mainstream class settings. Le rôle des enseignants dans la conception de tâches pertinentes en apprentissage des langues au moyen des TIC: Une réflexion sur l'apprentissage authentique pour les jeunes apprenants d’ALS. L'apprentissage par tâches continue d'évoluer au fur et à mesure que les outils et les approches pédagogiques inspirés des technologies de l'information et de la communication (TIC) permettent de transformer les expériences d'apprentissage des étudiants en stimulant leur motivation, leur sens de l'autonomie et, finalement, l’enrichissement de leur vocabulaire. Pour réaliser cette synergie, les enseignants devront réinventer l'apprentissage authentique et la conception des tâches. Cet article décrit et réfléchit aux changements d’exigences et de rôles de l'enseignant à l'école primaire. Un échantillon représentatif d'une série de tâches connectées fournit un modèle pour les futurs enseignants qui se lancent dans la préparation d’un travail sérieux pour les étudiants d’ALS, aujourd'hui de plus en plus nombreux dans l’enseignement général.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".