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Record W2157985956 · doi:10.1080/09500690010006554

The development and use of an instrument to assess students' attitude to the study of chemistry

2001· article· en· W2157985956 on OpenAlexaboutno aff
Judith Bennett

Bibliographic record

VenueInternational Journal of Science Education · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
FundersNational Research Foundation
KeywordsRemedial educationContext (archaeology)Mathematics educationScience educationPsychologyMultimethodologyData collectionAction researchSociologySocial science

Abstract

fetched live from OpenAlex

This paper reports on aspects of a three-phase study whose aim was to gather information on undergraduates' responses to the study of science. The emphasis of this paper is on methodological issues arising from considerations of how to measure and analyse data on attitudes. The study draws on the methodology employed in an earlier study undertaken in Canada, the Views on Science-Technology-Society (VOSTS) study, applying the methodology in a new context. The first two phases involved the development and validation of an appropriate research instrument. The third phase involved using the instrument with students in the first year of study at a South African University. In additional to the quantitative data gathered, the students' responses on the instrument were used to develop in-depth 'profiles' of particular groups of students. This technique proved particularly effective in identifying areas for possible remedial action.

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)0.023
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.144
GPT teacher head0.492
Teacher spread0.347 · 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 designObservational
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

Citations99
Published2001
Admission routes1
Has abstractyes

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