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Record W4402194801 · doi:10.1002/fer3.52

Unleashing creativity in STEM teacher education through scripting task pedagogy

2024· article· en· W4402194801 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

VenueFuture in Educational Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsCreativityScripting languageTask (project management)PedagogyMathematics educationPsychologyComputer scienceEngineeringProgramming languageSocial psychology

Abstract

fetched live from OpenAlex

Abstract This paper proposes a creative pedagogical approach that aims to foster authentic STEM teacher education through incorporating scriptwriting tasks in science and mathematics courses for future secondary STEM teachers. These tasks invite teachers to create imaginary dialogues addressing specific pedagogical challenges, such as conceptual difficulties, misconceptions, or unexpected questions arising during instruction. We assert that traditional approaches to lesson planning in STEM methods courses do not provide sufficient opportunity for exploring both content and pedagogy and fostering student engagement. Hence, we propose scriptwriting‐based pedagogy as an innovative and creative way of cultivating future STEM teachers' pedagogical content knowledge. This paper showcases three examples of scriptwriting tasks implemented in secondary STEM teacher education. We elucidate the pedagogical opportunities afforded by scriptwriting and underscore its pedagogical potential for STEM teacher education.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.243
GPT teacher head0.562
Teacher spread0.319 · 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