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Exercise Messengers: Exploring Student‐Learning Perceptions of a Science Animation Video using Q‐methodology

2020· article· en· W3017210407 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

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicQ Methodology Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAnimationPerceptionPsychologyStudent engagementAction (physics)PreferenceViewpointsEducational technologyMathematics educationMultimediaComputer science

Abstract

fetched live from OpenAlex

The utility of animation videos in teaching science to students has yielded mixed results, with some studies showing success in student engagement and performance, and others a lack thereof. While these discrepancies can be intrinsic to the type of video intervention, they may also be a result of the diverse learning perceptions within a given classroom. Some students may express higher engagement with animations, while others require additional tools for high‐level engagement to be reached. Q‐methodology combines qualitative and quantitative techniques to identify subjective viewpoints, thereby offering great potential to explore factors that may influence engagement with educational material. Using Q‐methodology and a knowledge retention assessment, we explored learning perceptions and performance of 31 elementary school‐aged children (16 boys and 15 girls aged 11 (SD=2) years) following the screening of an evidence‐based science animated video about exercise and bone physiology. We identified four salient learning perceptions within this sample, which were described as Engaged Learners, Action‐Takers, Interactive Learners, and Receptive Learners. We classified these perceptions based on student‐ranked statements related to video engagement, including knowledge attainment, action‐based thinking, enjoyment, learning preferences, and endorsement. Engaged Learners actively understood concepts explained in the video and promoted the use of the video as a learning tool in educational settings. Action‐Takers were able to reflect on the concepts in the video, and were motivated to change their behaviour based on the messaging of the video. Interactive Learners engaged least with the video while expressing a greater preference to discuss the content with their teacher. Lastly, Receptive Learners showed openness to the video, but still preferred traditional learning despite seeing utility in sharing the video with family and friends. The knowledge retention assessment showed that students scored an average of 79% (SD=16%), with 20/31 students performing above 80% on the assessment. We noted that Interactive Learners presented the lowest scores on knowledge retention relative to Engaged Learners and Receptive Learners ( p =0.0200), suggesting a relationship between perceptions and performance. Using a chalkboard animated video, we showed that perceptions influence engagement and knowledge retention of scientific content. Identifying learning perceptions can help educators, scientists, and anatomists alike to generate learning tools that will effectively engage students with various types of perceptions while taking into consideration their learning preferences. With this information, we can refine science animation videos and/or supplement them with additional learning tools, thereby optimizing science education for every student in the classroom. Support or Funding Information Natural Sciences and Engineering Research Council (NSERC)

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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)0.021
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.583
GPT teacher head0.506
Teacher spread0.077 · 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