Teaching L2 Learners How to Listen Does Make a Difference: An Empirical Study
Bibliographic record
Abstract
This study investigated the effects of a metacognitive, process‐based approach to teaching second language (L2) listening over a semester. Participants ( N = 106) came from six intact sections of French as a second language (FSL) courses. The experimental group ( n = 59) listened to texts using a methodology that led learners through the metacognitive processes (prediction/planning, monitoring, evaluating, and problem solving) underlying successful L2 listening. The control group ( n = 47), taught by the same teacher, listened to the same texts the same number of times but without any guided attention to process. Development of metacognition about L2 listening, tracked using the Metacognitive Awareness Listening Questionnaire (MALQ), was measured at the beginning, middle, and end points of the study. As hypothesized, the experimental group significantly outperformed the control group on the final comprehension measure, after we controlled for initial differences. The hypothesis that the less skilled listeners in the experimental group would make greater gains than their more skilled peers was also verified. Transcript data from stimulated‐recall sessions provide further evidence of a growing learner awareness of the metacognitive processes underlying successful L2 listening, as MALQ student responses changed over the duration of the study.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".