MétaCan
Menu
Back to cohort
Record W2910141384 · doi:10.3389/fpsyg.2018.02773

Differences in Attitudes Toward Reading: A Survey of Pupils in Grades 5 to 8

2019· article· en· W2910141384 on OpenAlexaffabout
Pascale Nootens, Marie‐France Morin, Denis Alamargot, Carolina Gonçalves, Michèle Venet, Anne-Marie Labrecque

Bibliographic record

VenueFrontiers in Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologyReading (process)Mathematics educationDevelopmental psychologyLinguistics

Abstract

fetched live from OpenAlex

Recent research on literacy has highlighted the impact of affective factors on learning to read. Among these factors, attitudes toward reading have been clearly shown to influence the development of reading skills and academic success. Nevertheless, differences in children's attitudes across schooling have yet to be properly documented, especially for the French language and the transition between elementary and secondary education. In this cross-sectional study, our goal was to gauge the attitudes of French-speaking pupils across this transitional period. We therefore administered a computer-based questionnaire to 469 pupils in Grades 5 to 8 in Quebec (Canada), to gather their views about leisure reading and academic reading. Results showed that their stated attitudes toward reading remained stable across the final 2 years of elementary school, as well as across the first 2 years of middle school, but differences were observed for the transition from one education level to the next, with stated attitudes toward reading being less positive in the latter. This effect, which was observed for both leisure and academic reading, concerned girls and boys alike. We discuss possible explanations for these differences in reading attitudes at this juncture in children's schooling.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.360
Teacher spread0.306 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations41
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in PsychologySame topicReading and Literacy DevelopmentFrench-language works237,207