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Record W2784780785 · doi:10.36510/learnland.v11i1.932

Inclusive Teaching With Digital Technology: Supporting Literacy Learning in Play-Based Kindergartens

2018· article· en· W2784780785 on OpenAlex
Monica McGlynn-Stewart, Leah Brathwaite, Lisa Hobman, Nicola Maguire, Emma Mogyorodi, Yeh Uhn Park

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

VenueLEARNing Landscapes · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsToronto Metropolitan UniversityGeorge Brown College
Fundersnot available
KeywordsLiteracyMathematics educationPedagogyComputer sciencePsychologyDigital literacyMultimedia

Abstract

fetched live from OpenAlex

Young children who are English Language Learners or have special learning needs can find it difficult to communicate in kindergarten classrooms. Open-ended tablet applications offer multi-modal tools for these children to communicate their ideas, engage with others, and demonstrate and develop their knowledge and skills. They position students as the producers and creators of the literacy content. Using pedagogical strategies such as effective routines, opportunities to collaborate and share with peers, and modelling, kindergarten educators can employ open-ended iPad apps to support the literacy and digital learning of children who are English Language Learners or who have special learning needs.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.277
Teacher spread0.271 · 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