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Record W1970614302 · doi:10.1177/1476750307083716

Action research in teacher education

2008· article· en· W1970614302 on OpenAlexaff
Julian Kitchen, Dianne Stevens

Bibliographic record

VenueAction Research · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of TorontoBrock University
Fundersnot available
KeywordsAction researchTeacher educationPedagogyAction (physics)Professional developmentMathematics educationReflection (computer programming)PsychologyReflective practiceComputer science

Abstract

fetched live from OpenAlex

Two teacher-educators, an instructor and a teaching assistant, designed an action research project focused on enhancing their professional practice and the practice of their students by introducing the preservice teachers to action research. Both teacher-educators viewed this decision as progressive and emancipatory, as action research encourages inquiry and reflection, connects theory to practice, and creates links between preservice and in-service teaching. Simultaneously, the teacher-educators integrated preservice curriculae, modeling the enriched teaching and learning that can result from an interdisciplinary approach. Data include preservice teachers' action research proposals, reports and reflections, as well as the teacher-educators' reflections and collaborative conversations. Instructors used self-study methodology to reflect on their effectiveness in enhancing the professional lives of their students and themselves. A significant number of preservice teachers indicated that engaging in action research expanded their conceptions of teaching; such expansion holds potential for fostering change in schools.

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)0.116
metaresearch head score (Gemma)0.100
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 score0.116
Threshold uncertainty score0.613

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1160.100
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0100.009
Science and technology studies0.0060.078
Scholarly communication0.0190.016
Open science0.0050.010
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0110.001

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 head0.856
GPT teacher head0.669
Teacher spread0.187 · 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

Citations89
Published2008
Admission routes1
Has abstractyes

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