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Record W601038434

Visualizing the complexity of the molecular world: examining the role of animated representations in the development of undergraduate students' understanding of dynamic cellular events

2012· dissertation· en· W601038434 on OpenAlexaff
Earl Woodruff, Jodie Anne Jenkinson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAnimationAgency (philosophy)Event (particle physics)NarrativeVisualizationPsychologyComputer scienceMathematics educationArtificial intelligenceLinguisticsEpistemologyComputer graphics (images)
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the relative effectiveness of three-dimensional visualization techniques for learning about protein conformation and molecular motion in association with a ligand and receptor binding event. Increasingly complex versions of the same binding event were depicted in each of four animated treatments. Students (n = 131) were tested at three time points, and over both the short and longer term, the most complex of the four animated treatments was the most successful at fostering students' understanding of the events depicted. A follow-up study including eight biology students was conducted to gain greater insight into the students' underlying thought processes and better characterize their understanding of the animated representations. Analysis of verbal reports and eye tracking data suggest that students are able to attend to the same narrative elements regardless of the level of complexity depicted in each animation. Analysis of verbal protocol data revealed a positive correlation between the number of explanatory statements expressed by participants and the complexity of the animation viewed. As well, prior knowledge was positively correlated with the number of explanatory statements contained in each protocol. Overall, students demonstrated an understanding of protein conformation and molecular crowding. However results suggest that students have difficulty understanding and associating randomness with molecular events. The verbal reports contained several instances of students' attaching agency to protein and ligand, anthropomorphizing their movements and subsequent binding. Ordinarily cellular events, owing to their sheer complexity, are depicted in a highly schematized, simplified form. The results of this study would suggest that under select circumstances this may not be the most appropriate approach to depicting dynamic events. However additional attention must be given to exploring techniques that can satisfactorily balance the random nature of molecular events with narrative explanations of these processes.

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)0.002
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.366
Teacher spread0.302 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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