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Record W2103307374 · doi:10.1111/bjet.12329

Enhancing <scp>L</scp> 2 vocabulary acquisition through implicit reading support cues in e‐books

2015· article· en· W2103307374 on OpenAlex
Yeu‐Ting Liu, Aubrey Neil Leveridge

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.

Bibliographic record

VenueBritish Journal of Educational Technology · 2015
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of British Columbia
FundersNational Taiwan UniversityMinistry of Science and Technology, Taiwan
KeywordsVocabularySubliminal stimuliReading (process)Priming (agriculture)Computer sciencePsychologySensory cueCognitive psychologyLinguistics

Abstract

fetched live from OpenAlex

Abstract Various explicit reading support cues, such as gloss, QR codes and hypertext annotation, have been embedded in e‐books designed specifically for fostering various aspects of language development. However, explicit visual cues are not always reliably perceived as salient or effective by language learners. The current study explored the efficacy of implicit reading support cues—cues that are imperceptible to second‐language ( L 2) readers during their L 2 digital reading—for promoting L 2 vocabulary acquisition. Results suggest that subliminal formal priming—being one type of implicit reading support cues—helped L 2 readers significantly improve their form‐meaning vocabulary knowledge through e‐book reading. In particular, subliminal formal priming was more effective when the digital content, including the text and relevant illustration, was presented to L 2 readers simultaneously, rather than incrementally. The results have important implications vis‐à‐vis the need for the inclusion of implicit reading cues, and the optimal digital input presentation mode for enhancing L 2 vocabulary gains.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.754

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.321
Teacher spread0.301 · 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