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Record W4407998546 · doi:10.3390/educsci15030296

Insights and Challenges for Educational Leaders Supporting Families in Home Reading Practices

2025· article· en· W4407998546 on OpenAlexaff
Mark Colgate, Orla Colgate

Bibliographic record

VenueEducation Sciences · 2025
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsReading (process)Mathematics educationPedagogyPsychologySociologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Educational leadership plays a pivotal role in fostering effective home reading practices for families with children in kindergarten to Grade 2. This study examines the literacy environments of 135 families across four schools and includes in-depth interviews with 20 parents to identify key challenges in early reading development. The findings reveal that many parents struggle with supporting their children in decoding unfamiliar words, establishing consistent reading habits, and understanding the reading acquisition process. The research highlights the need for targeted guidance and structured strategies to enhance home literacy practices. School leaders and educators are essential in bridging the gap between classroom instruction and home reading support. By strengthening family–school partnerships, enhancing parental engagement, and implementing sustainable systems, educational leaders can empower families and improve early reading outcomes. This study provides practical recommendations for school leaders and administrators to create environments that support collaborative reading efforts, ensuring that children receive the necessary reinforcement both in school and at home.

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)0.013
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.004
Scholarly communication0.0070.005
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.122
GPT teacher head0.455
Teacher spread0.333 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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