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Record W7046728463

Education for Sustainable Development through Socioscientific Issues:Pre-service Teachers’ Pedagogical Design Capacity

2024· article· en· W7046728463 on OpenAlexfundno aff

Bibliographic record

VenueTU/e Research Portal · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersDirectorate for STEM EducationNational Institutes of HealthEkiti State UniversityUniversity College LondonMontclair State UniversityWestern Washington UniversityMount Royal UniversityUniversity of South Carolina
KeywordsSustainabilitySustainable developmentProfessional developmentReflection (computer programming)Qualitative researchField (mathematics)Capacity buildingEducation for sustainable developmentFaculty development
DOInot available

Abstract

fetched live from OpenAlex

Even though the importance of sustainability has been recognized in education, teachers struggle with identifying an appropriate method to implement education for sustainable development (ESD) in STEM subjects. There is a relatively large literature on ESD, and the implementation of socioscientific issues (SSI) separately. However, there is limited research on using SSI for ESD. For this reason, this empirical study aims at characterizing STEM teacher candidates’ pedagogical design capacity (PDC) to address what resources they use, and how they interact with these resources to design SSI-based instruction to facilitate ESD. The qualitative data is collected through field notes, reflection reports and semi-structured interviews. The results reveal that during their design, pre-service teachers referred to teacher resourcesthe most, followed by collaborative resources, and instructional resources. Even though their use of resources shows strong connections between SSI and their pedagogical content knowledge, pre-service teachers’ consideration regarding assessment remains inadequate. Furthermore, this study shows that professional development sessions have the potential to foster pre-service teachers’ use of PDC resources to address ESD.

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 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)0.003
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0740.000

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 head0.207
GPT teacher head0.453
Teacher spread0.246 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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