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Record W3087960878

TACKLING THE SHORTAGE OF PHYSICS TEACHERS

2020· article· en· W3087960878 on OpenAlexaboutno aff
Elizabeth Angstmann

Bibliographic record

VenueProceedings of The Australian Conference on Science and Mathematics Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortagePhysics educationCertificateMathematics educationQuarter (Canadian coin)Science educationMedical educationPsychologyMathematicsMedicineGeography
DOInot available

Abstract

fetched live from OpenAlex

Young professionals with STEM skills are in high and increasing demand. Unfortunately, there is a prevalent gender disparity among graduates in engineering and physics. Girls are opting out of studying physics before the end of year 10: less than one quarter of the year 11 and 12 physics cohort in NSW is female. Physics trained high school teachers are needed to engage students in junior secondary science. However, there is currently a state, national and global shortage of such teachers, which is particularly acute in regional schools. Having a conceptual focus and contextualising material has been shown to have a positive impact on students’ “physics identity” and consequently their interest in a STEM career. Teachers need a good understanding of physics themselves in order to design engaging classes for students. To address this shortage, UNSW has introduced an online Graduate Certificate in Physics for Science Teachers, which is now in its third year. Feedback from graduandates has been very positive: some have secured jobs in regional schools, many have commented on the impact it has had on their teaching of junior science, and some have shared resources they developed with colleagues.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.121
GPT teacher head0.385
Teacher spread0.264 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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