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Record W2075542165 · doi:10.3138/cmlr.58.4.555

'It Was Nice to See That Our Predictions Were Right': Developing Metacognition in L2 Listening Comprehension

2002· article· en· W2075542165 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMetacognitionActive listeningPsychologyTask (project management)Formative assessmentListening comprehensionComprehensionMathematics educationArgument (complex analysis)Cognitive psychologyCognitionComputer scienceCommunication

Abstract

fetched live from OpenAlex

Beginning-level core French students (Grades 4-6) completed listening comprehension tasks and reflective exercises, using instruments that engaged the students in prediction, evaluation, and other processes involved in listening. Following each task and accompanying exercises, students completed a questionnaire on the formative qualities of the activities and instruments. Results of this qualitative study suggest that use of these instruments helped sensitize students to the processes underlying L2 listening comprehension and tapped their metacognitive knowledge. Student comments evidenced a high degree of task and strategic knowledge and, to a lesser degree, person knowledge. Evidence from this study supports the argument that reflection on the processes of listening can help students develop metacognitive knowledge and, potentially, achieve greater success on these types of L2 listening tasks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.049
GPT teacher head0.250
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it