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Record W4291535658 · doi:10.1017/s1366728922000542

Tracking reading development in an English language university-level bridging program: evidence from eye-movements during passage reading

2022· article· en· W4291535658 on OpenAlexafffund
Daniel Schmidtke, Sadaf Rahmanian, Anna L. Moro

Bibliographic record

VenueBilingualism Language and Cognition · 2022
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsBridging (networking)Reading comprehensionReading (process)Eye movementEye trackingLiteracyComprehensionPsychologyComputer scienceMathematics educationLinguisticsPedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Increasing numbers of international students enter university education via English language bridging programs. Much research has overlooked the nature of second language reading development during a bridging program, focusing instead on the development of literacy skills of international students who already meet the language requirement for undergraduate admission. We report a longitudinal eye-movement study assessing English passage reading efficiency and comprehension in 405 Chinese-speaking bridging program students. Incoming IELTS reading scores were used as an index of baseline reading ability. Linear mixed-effects regression models fitted to global eye-movement measures and reading comprehension indicated that despite initial between-subjects differences, within-subject change at each ability level progressed at the same rate, following parallel growth trajectories. Therefore, there was significant overall reading progress during the bridging program, but no evidence that the gap between low and high ability readers either closed or widened over time.

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 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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.319
Teacher spread0.284 · 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 teacher head, not a consensus.

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

Citations5
Published2022
Admission routes2
Has abstractyes

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