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Record W1566535076

Inquiry based learning in University school outreach program

2014· article· en· W1566535076 on OpenAlexaboutno aff
Tom Gordon, Manjula Sharma, Helen Georgiou

Bibliographic record

VenueProceedings of The Australian Conference on Science and Mathematics Education (formerly UniServe Science Conference) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Assessment and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsWorksheetOutreachSyllabusMathematics educationCurriculumQuarter (Canadian coin)PsychologyPedagogyMedical educationMedicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND The aim of this project is to examine the effect of including inquiry based learning activities into the education outreach program run by the Sydney University School of Physics called Kickstart Physics. Kickstart Physics sees approximately a quarter of the total number of students that sit the NSW HSC Physics examination. The rationale for the project was to utilise the large percentage of participants and include inquiry, which is advocated in the mandatory NSW curricula and is recognized as an appropriate pedagogy for school science. APPROACH A worksheet outlining an activity/experiment is handed out to half the students while the other half receive a worksheet designed on inquiry-based learning. The learning outcomes are the same for the two groups and syllabus dot points are the same. Some 1000 year 12 school students are surveyed. The project considers how students arrive at different inquiry-based outcomes such as making hypotheses, displaying and interpreting data, validity, reliability. RESULTS and CONCLUSIONS The design of the worksheets are critical for eliciting elements of inquiry in comparison to learning sequential content with the normal worksheets.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.005
Scholarly communication0.0010.002
Open science0.0020.000
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 head0.094
GPT teacher head0.388
Teacher spread0.295 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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