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Record W3017172981 · doi:10.1017/s0272263120000091

YOUNG LEARNERS’ PROCESSING OF MULTIMODAL INPUT AND ITS IMPACT ON READING COMPREHENSION

2020· article· en· W3017172981 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in Second Language Acquisition · 2020
Typearticle
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsCarleton University
FundersUniversitat de Barcelona
KeywordsReading (process)Reading comprehensionComprehensionActive listeningVariety (cybernetics)Eye movementComputer sciencePsychologyTest (biology)Cognitive psychologyListening comprehensionLinguisticsMultimediaCommunicationArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Theories of multimedia learning suggest that learners can form better referential connections when verbal and visual materials are presented simultaneously. Furthermore, the addition of auditory input in reading-while-listening conditions benefits performance on a variety of linguistic tasks. However, little research has been conducted on the processing of multimedia input (written text and images) with and without accompanying audio. Eye movements were recorded during young L2 learners’ ( N = 30) processing of a multimedia story text in reading-only and reading-while-listening conditions to investigate looking patterns and their relationship with comprehension using a multiple-choice comprehension test. Analysis of the eye-movement data showed that the presence of audio in reading-while-listening conditions allowed learners to look at the image more often. Processing time on text was related to lower levels of comprehension, whereas processing time on images was positively related to comprehension.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.361
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.408
Teacher spread0.359 · 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