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Record W1581105494 · doi:10.22329/jtl.v7i1.563

Facilitating “Gem Moments” of Learning: Reading Research as Teacher Professional Development

2010· article· en· W1581105494 on OpenAlexvenueaboutno aff
Sarah Twomey

Bibliographic record

VenueJournal of Teaching and Learning · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive reframingReading (process)Professional developmentProfessional learning communityPedagogyUnit (ring theory)Mathematics educationLearning to readPsychologyFocus groupSociologyLinguisticsLiteracySocial psychology

Abstract

fetched live from OpenAlex

This purpose of this paper is to deepen our understanding of a relational model of professional development that nurtures teachers’ interest in learning and professional growth through reading. This case study documents the impact of a teacher reading group that was created for the purposes of a larger study between 2005 and 2007 in Vancouver, British Columbia, Canada. Louisa, one of the six participants of this larger study, is the focus of this paper. Louisa’s practice of reading, interpreting, evaluating, and utilizing the on-line research she read individually and collectively with the other five participants of the study became a way for her to identify and critique important issues, reframe her experiences as a teacher, question her professional assumptions and beliefs, and begin to develop a new unit of study for her English as a Second Language students.

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)0.028
metaresearch head score (Gemma)0.040
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 score0.028
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.040
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0140.032
Scholarly communication0.0180.013
Open science0.0030.017
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 head0.062
GPT teacher head0.361
Teacher spread0.299 · 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

Citations3
Published2010
Admission routes2
Has abstractyes

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