MétaCan
Menu
← Back to cohort
Record W2611323150

How to Teach les Êtres Humains: An Investigation into Teachers’ Understandings of Learner Empowerment in Ontario Secondary School Core-French Classrooms

2017· article· en· W2611323150 on OpenAlexaboutno aff
Oliver P Drigo

Bibliographic record

VenueTSpace (University of Toronto) · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPedagogySociologyMathematics educationPsychology
DOInot available

Abstract

fetched live from OpenAlex

In keeping with the spirit of renewed efforts in French as a Second Language education in Ontario, it has become increasingly apparent of the need to expand upon traditional desired outcomes, namely in developing more confident, proficient and successful French learners. To better conceptualize these enhanced expectations, ideas of learner empowerment — a more expansive and inclusive form of motivation that comprises feelings of competency and self-efficacy — were applied to an investigation of reported classroom practices of French teachers. A qualitative research approach was used that combined a literature review with semi-structured, face-to-face interviews with two secondary-school Core French teachers. A theoretical framework — Ryan and Deci’s Self-Determination Theory — was applied to improve understanding of teachers’ reported learner empowerment practices. Drawing connections between the compiled data and the literature reviewed, analysis yieled four main themes: understandings of ‘empowerment’; reported efforts to empower learners; factors reportedly influencing learner empowerment; and encouragement of students’ continued interest in French. Ultimately, findings suggest that some teachers might lack the support, encouragement, or even accountability necessary in going beyond the traditional ‘disempowering’ norms of the Core French classroom, and that some teachers may not fully appreciate nor fulfill the important social role that they have on student empowerment in the Core French classroom

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0130.012
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.258
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)→Same topicEFL/ESL Teaching and Learning→French-language works237,207→