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Scientists and Science Educators Mentoring Secondary Science Teachers

2010· article· en· W2061865125 on OpenAlexaff
Jerine Pegg, Heidi I. Schmoock, Edith Gummer

Bibliographic record

VenueSchool Science and Mathematics · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsScience educationMathematics educationPedagogySecondary educationPsychologySociology

Abstract

fetched live from OpenAlex

This paper examines secondary science teachers' perspectives of the role that mentoring by a scientist and science educator pair played in their professional development. Multiple data sources from three years of a professional development project, including interviews, participant reflections, and a focus group, were used to examine the benefits, supporting characteristics, and challenges of the mentoring relationship. Results indicated that primary benefits of the mentoring included assistance in translating science content and inquiry-based pedagogy from the professional development into practice and breaking the isolation felt by secondary science teachers. Specific characteristics that were found to support the teachers in the mentoring relationship included: (1) mentors who were seen as objective, outside observers; (2) a sustained relationship with the mentors; and (3) accountability. Challenges included matching scientists' and science educators' content expertise with teachers' curriculum and the negotiation of roles and expectations between the teachers and mentors.

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)0.011
metaresearch head score (Gemma)0.033
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0080.002
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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