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Record W2134277310 · doi:10.1080/03057260903142269

A tool for changing the world: possibilities of cultural‐historical activity theory to reinvigorate science education

2009· article· en· W2134277310 on OpenAlexaff
Wolff‐Michael Roth, Yew‐Jin Lee, Pei‐Ling Hsu

Bibliographic record

VenueStudies in Science Education · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsExplicationEpistemologyScholarshipSociologyDialecticActivity theoryEmotiveOntologySocial sciencePedagogyPhilosophy

Abstract

fetched live from OpenAlex

Cultural‐historical activity theory, an outcrop of socio‐psychological approaches toward human development, has enjoyed tremendous growth over the past two decades but has yet to be appropriated into science education to any large extent. In part, the difficulties Western scholars have had in adopting this framework arise from its ontology, which is materialist dialectical and, hence, does not allow easy absorption into non‐dialectical (classical logical) thinking underlying much of Western scholarship. Cultural‐historical activity theory has tremendous potential because it sublates traditional dichotomies in everyday teaching‐learning situations including individual/collective, body/mind, intra‐/inter‐psychological, cognitive/emotive and psychological/sociological. In this contribution, we not only review the existing literature that uses or develops this non‐dualistic approach, but also articulate an intelligible explication of the theory that is more accessible to Western scholars and describe possible future curriculum work and research in science education as an expression of the fruitfulness of the theory.

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)0.006
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0040.045
Scholarly communication0.0110.017
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.128
GPT teacher head0.515
Teacher spread0.386 · 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 designTheoretical or conceptual
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

Citations78
Published2009
Admission routes1
Has abstractyes

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