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Learners are masters: The karaoke as an ergonomic dispositif for foreign languages learning

2024· article· en· W4405576219 on OpenAlexaboutno aff
Leïla G-Blili

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)Foreign languagePerspective (graphical)Human factors and ergonomicsComputer scienceMultimediaMathematics educationPsychologyHuman–computer interactionKnowledge managementArtificial intelligencePoison controlMedicine

Abstract

fetched live from OpenAlex

The IT landscape is expanding and teaching strategies need to adapt, which tends to recognise an ergonomic perspective for education. The interest of our study is based on the ergonomics of technology for foreign language learning. We undertook fieldwork and data collection with first-year students in Canada to explore the potential of karaoke. We drew on Dörnyei’s (2014) retrodictive methodology, analysing non-probabilistic data collected from elective participants learning English as a foreign language. The results show that learners tend to develop a sense of self-efficacy. Furthermore, it appears that the ergonomic design of the device allows for adaptation to the learner, ultimately facilitating its adoption for personal use. This preliminary research is currently being developed further to explore the matter in greater depth.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.363
Teacher spread0.329 · 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
Published2024
Admission routes1
Has abstractyes

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