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Record W4410380729 · doi:10.26434/chemrxiv-2025-kzdv9

Visual skills in the arts and their potential in chemistry education

2025· preprint· en· W4410380729 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemRxiv · 2025
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicEducational Research and Science Teaching
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsChemistry educationPsychologyMathematics educationVisual artsChemistryArtSocial psychology

Abstract

fetched live from OpenAlex

The necessity of visuals in chemistry underscores the importance of representational competence in chemistry education, which encompasses the ability to interpret and generate visual representations. Yet, chemistry does not have a tradition of training students directly in the general skills of visual analysis or drawing. The challenges faced by students in understanding complex visuals could be addressed by looking for parallels in other disciplines. In this study, we used the parallel processes framework to explore the shared cognitive skills between chemistry and two arts disciplines: fine arts and art history. By exploring how observation, analysis, modelling, and interpretation function in both fields using an action-research approach, we propose three parallel processes: visual analysis, visuospatial reasoning, and drawing. We then designed activities based on these skills for a focus group with science instructors to provide insight into their potential and feasibility for post-secondary classrooms. We show the need for diverse teaching approaches, particularly in interpreting three-dimensional representations, and the importance of scaffolding visual analysis activities. Overall, this research contributes to the ongoing discourse on representational competencies in science education.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.316
Teacher spread0.296 · 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