MétaCan
Menu
Back to cohort
Record W4413183936 · doi:10.64152/10125/73566

English L2 vocabulary learning with clickers: Investigating pedagogical effectiveness

2024· article· en· W4413183936 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLanguage learning & technology · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsComputer scienceVocabularyVocabulary learningVocabulary developmentEducational technologyLanguage acquisitionNatural language processingMathematics educationPsychologyTeaching methodLinguisticsMultimedia

Abstract

fetched live from OpenAlex

A growing body of literature on the pedagogical effectiveness of clickers in a second language (L2) context has revealed that clickers can promote learning. However, the extent to which clickers play a role in L2 acquisition compared to other pedagogical approaches lacks consensus; in addition, most research has focused on adult learners and has taken place in large classrooms. To address these limitations, the current research investigated the effects of clickers on L2 vocabulary acquisition in a K-12 educational setting. Two intact groups of Grade 8 students learning L2 English were assigned to a treatment: while the Clicker Group (n = 31) received instruction via clickers, the Non-Clicker Group (n = 30) was treated via hand-raising without the target technology. The pedagogical effectiveness of clickers on participants’ acquisition of the target vocabulary was measured via pretests, posttests and delayed posttests. Overall, the results indicate that vocabulary acquisition was comparable in both groups. The discussion of the findings explores the role of individual differences among users (i.e., some participants improved significantly more than others) and highlights the implications of the study for L2 teaching/learning.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.022
GPT teacher head0.272
Teacher spread0.250 · 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