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Record W4389128693 · doi:10.55016/ojs/ajer.v66i3.56988

Moving the Needle on Literacy: Lessons Learned from a School Where Literacy Rates Have Improved Over Time

2020· article· en· W4389128693 on OpenAlexaffvenue
George K. Georgiou, Greg Kushnir, Rauno Parrila

Bibliographic record

VenueAlberta Journal of Educational Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsWorkers Compensation Board of AlbertaUniversity of Alberta
Fundersnot available
KeywordsPsychologyLiteracyReading (process)Formative assessmentMathematics educationPedagogyData collectionGrounded theoryProfessional developmentMedical educationQualitative researchSociology

Abstract

fetched live from OpenAlex

Literacy is the most important skill children are required to master during their early school life. At the same time, much has been written about both the inadequate preparation of teachers to teach reading and the ever-increasing number of poor readers in our schools. In this study, we examined teachers’ perceptions of the factors that have contributed to their school’s success in improving children’s literacy scores. We used a sequential explanatory mixed methods research design where Phase 1 involved collecting quantitative data to document the improvement in reading and asking the teachers to fill out a questionnaire, while Phase 2 comprised gathering qualitative data where the principal and a language arts teacher commented on the findings from Phase 1. The results revealed three important themes that teachers perceive contributing to their school’s success. First, teachers collaborate weekly on their own learning, plan instruction together, and provide support for each other. Second, formative assessments are shared within each grade and data are used to inform areas of growth, not to evaluate teachers’ performance. Third, the school focuses on improving reading and believes in the child’s continuous growth. Taken together, the findings of our study suggest that teachers perceive success to be a team effort grounded on theory and the principles of collaborative learning. Keywords: children, literacy, mixed methods, reading, professional development. La littératie constitue l’habileté la plus importante que les enfants doivent maitriser pendant leurs premières années à l’école. Parallèlement, on a beaucoup écrit sur la préparation inadéquate des enseignants en matière d’enseignement de la lecture et sur le nombre croissant d’élèves avec des compétences insuffisantes en lecture. Dans cette étude, nous avons examiné les perceptions qu’ont les enseignants des facteurs ayant contribué à la réussite de leur école dans l’amélioration des compétences des élèves en lecture. Nous avons employé un modèle exploratoire et séquentiel de recherche à méthodes mixtes. Pendant la première phase, nous avons recueilli des données quantitatives afin de documenter l’amélioration en lecture et avons demandé aux enseignants de compléter un questionnaire. La deuxième phase a consisté en la cueillette de données qualitatives ou le directeur de l’école et l’enseignant de langue ont commenté les résultats de la première phase. Les résultats ont révélé trois thèmes importants relatifs aux perceptions des enseignants quant à la réussite de leur école. En premier lieu, les enseignants collaborent de façon hebdomadaire sur leur propre développement, planifient les cours ensemble et s’appuient mutuellement. Deuxièmement, on partage les évaluations formatives entre enseignants de la même année et on étudie les données pour identifier les aspects à améliorer, pas pour évaluer la performance des enseignants. Troisièmement, l’école mise sur l’amélioration de la lecture et croit en l’épanouissement continu des élèves. Globalement, les résultats de notre étude indiquent que les enseignants perçoivent la réussite comme découlant d’un effort collectif ancré dans la théorie et les principes de l’apprentissage collaboratif. Mots clés : enfants, littératie, méthodes mixtes, lecture, développement professionnel

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)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.537
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0290.001

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 head0.105
GPT teacher head0.468
Teacher spread0.363 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2020
Admission routes2
Has abstractyes

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