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Record W4239565827 · doi:10.24124/2013/bpgub1571

Inquiry for deep learning for all learners

2013· dissertation· en· W4239565827 on OpenAlexaff
Nicole R. Davey

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversity of Northern British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsFormative assessmentPedagogyResource (disambiguation)The artsPoint (geometry)Mathematics educationReflection (computer programming)Language artsEnglish languagePsychologyComputer scienceVisual artsArt

Abstract

fetched live from OpenAlex

This study, a retrospective reflection of a teacher's development, culminates in the design of a resource for educators, focusing on the use of professional inquiry to drive change in senior secondary BC English Language Arts classrooms. The materials are designed to help classroom teachers incorporate formative assessment and deep learning into their practice, reflect on the results for students, and adjust as needed to improve student outcomes. The study includes a rationale for changing pedagogy and a description of how inquiry enabled change in the author's English classroom and what that changed looked like. As a teacher leader who has made meaningful and lasting changes in her beliefs and practices, the author invites other teachers to use this resource as a starting point for their own inquiry into how classrooms and outcomes can be transformed. --Leaf ii.

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)0.003
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0070.004
Open science0.0010.007
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0180.006

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 head0.061
GPT teacher head0.416
Teacher spread0.355 · 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
Published2013
Admission routes1
Has abstractyes

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