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Record W2257928944

Activity-theoretical research on science teachers' expertise and learning

2010· article· en· W2257928944 on OpenAlex

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.

Bibliographic record

VenueInternational Conference of Learning Sciences · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLearning sciencesEmpirical researchMathematics educationScience educationEducational technologyExperiential learningActivity theoryPedagogyScience learningComputer sciencePsychologyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

Teachers serve as critical mediators of student learning. As such, teachers' expertise and learning remain important foci for theoretical development and empirical research. Cultural-historical activity theory (CHAT) has been forwarded as an underutilized but potentially powerful tool for educational research, including teachers' expertise, practice, and learning. However, as yet, little CHAT-based research has been undertaken focused on science teachers and teaching. In this paper, we draw upon two such empirical studies in which CHAT was used as an explicit theoretical and analytical framework to explore CHAT-based perspectives on science teacher learning. We present findings from these studies to highlight important themes in CHAT-based research on science teachers' learning in and from practice. These findings can not only inform programmatic efforts to better promote teachers' learning, but also theoretical perspectives on science teachers' expertise, practice, and learning across the science education and learning sciences communities.

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)0.020
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.014
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.248
GPT teacher head0.539
Teacher spread0.292 · 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