Language Learner Autonomy in Ontario's ESL Context
Bibliographic record
Abstract
Since its emergence in the early 1980’s, the notion of learner autonomy has not only become a buzzword in second language education literature but a revolutionary phenomenon affecting teaching/learning approaches across the world. A great number of countries have adopted measures to promote learner autonomy in their language schools. In Europe, for instance, the Council of Europe developed the Common European Framework of Reference for Languages (CEFR) and the European Language Portfolio (ELP) with the explicit goal of developing language learner autonomy (Little, 2007). In Canada, following the introduction of Manitoba Collaborative Language Portfolio Assessment (CLPA), very recently Portfolio-Based Language Assessment (PBLA) has been introduced and gradually implemented in government-funded ESL programs across the country (Pettis, 2014) to realize the same goal.\nGiven its importance, this study investigated the present status of the promotion of language learner autonomy in Ontario’s ESL context. To this end, through a mixed methods research design using interviews and surveys, the study explored the perceptions of ESL teacher trainers, ESL instructors, and ESL learners. Based on David Little’s comprehensive theory of language learner autonomy (2009), the study presents a thorough understanding of participants’ perceptions of the construct of learner autonomy, desirability, feasibility, and challenges of promoting learner autonomy, its contribution to second language learning and teachers’ roles in the context. The study furthers delves into the perceptions of introduction, and implementation of PBLA and discusses its shortcomings and advantages. It further suggests implications for practice regarding the promotion of language learner autonomy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".