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Record W3010481941

How Do Elementary Teachers Study and Learn from a Multimedia Model of Reading Development? An Exploratory Eye-Tracking Study.

2019· article· en· W3010481941 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2019
Typearticle
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsQueen's University
Fundersnot available
KeywordsReading (process)Eye trackingExploratory researchTask (project management)Tracking (education)Mathematics educationPsychologyMultimediaQualitative researchComputer sciencePedagogy
DOInot available

Abstract

fetched live from OpenAlex

This exploratory study used eye-tracking methodology to examine how elementary teachers study a multimedia model of reading development. Seven experienced teachers and 11 pre-service teachers participated. Visual attention, prior knowledge, and post-task scores were analyzed using quantitative and qualitative methods. Significant differences between the two groups were found with respect to fixations, scan paths, and pre- and post-task scores. Where experienced teachers focus their attention and the paths of their visual behaviour can inform the design of material that supports novice teachers’ understanding of how children learn to read. Keywords: teacher learning, multimedia learning, eye-tracking methodology, reading development, reading instruction

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)0.000
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 score0.264
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.077
GPT teacher head0.345
Teacher spread0.269 · 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