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Record W3185466589 · doi:10.1080/01443410.2021.1953445

Linking student, home, and school factors to reading achievement: the mediating role of reading self-efficacy

2021· article· en· W3185466589 on OpenAlexaffabout
Fu Chen, Alfred Sakyi, Ying Cui

Bibliographic record

VenueEducational Psychology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of AlbertaAlberta Advanced Education
Fundersnot available
KeywordsReading (process)PsychologyStructural equation modelingMultilevel modelReading motivationPerspective (graphical)Self-efficacyAcademic achievementLiteracyDevelopmental psychologySocial psychologyPedagogy

Abstract

fetched live from OpenAlex

Based upon the ecological perspective and the social cognitive theory, this study examined the role of reading self-efficacy in the associations of contextual factors with reading achievement by establishing an educational ecology of reading. The model included student factors, student/home factors, student/school factors, and school factors of reading. These contextual factors were hypothesised as predictors of reading self-efficacy, which was, in turn, the predictor of reading achievement. The Canadian data of the Progress in International Reading Literacy Study 2016 with 18,624 Grade 4 students from 926 schools were analysed with multilevel structural equation modelling. Results showed that most student- and school-level factors significantly predicted reading self-efficacy, which in turn significantly predicted reading achievement. Home resources for learning and school climate factors showed the strongest associations with reading. The theoretical and practical implications of our findings were discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.420
Teacher spread0.373 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2021
Admission routes2
Has abstractyes

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