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Record W4408959600 · doi:10.1007/s44217-025-00454-1

Comparing physical analogue and traditional videos for learning and emotional engagement

2025· article· en· W4408959600 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.

Bibliographic record

VenueDiscover Education · 2025
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsCanada Research ChairsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsPsychologyMultimediaCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

The lack of diversity in science, technology, engineering, and mathematics (STEM) fields is a vital issue that carries into the workforce. This study aims to enhance underrepresented students’ learning experience and emotional engagement by replacing mathematical abstractions with physical analogues. In the context of a post-secondary STEM course, we developed four video modules to compare the effects of physical analogues against a more traditional framing and assessed both the impact on learning and students’ emotional engagement with the material. Results suggest that the physical analogue videos significantly increased students’ emotional engagement, with more impact for women and non-native English speakers than for men and native speakers. Furthermore, students from other disciplines who were taking the course as part of their minor program found the physical analogue videos to be more helpful than the traditional videos in terms of understanding the course content. Students also suggested that compared to the traditional videos, the physical analogue versions helped them build mental models through visualization and analogies. However, we observed no statistical evidence that student performance on quizzes varied between the two treatments.

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)0.000
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 score0.839
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.055
GPT teacher head0.379
Teacher spread0.324 · 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