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Assessing the Relationship Between Students’ Approaches to Learning, Visuospatial Abilities, and Performance in an Undergraduate Human Anatomy Course

2020· article· en· W3017082105 on OpenAlexaff
Sean McWatt

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyTest (biology)KinesiologyCognitive psychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

Learning is difficult to quantify. Several metrics for successful student learning have been explored, the most popular of which is academic performance. However, academic performance does not always accurately represent nuanced outcomes such as meaningful learning and skill development, nor is it a successful predictor of long‐term knowledge retention. One metric that has demonstrated alignment with such qualitative learning outcomes is student approach to learning; a framework that evaluates the depth with which students interact with their learning environment and the course content. However, the student approach to learning framework has yet to be adequately investigated for its reliability as a metric for learning in human anatomy, specifically. One measure that has been shown to predict learning achievement in human anatomy is visuospatial ability. Individuals with high visuospatial abilities are typically faster and more successful at performing three‐dimensional anatomy tasks than those with low visuospatial abilities. It has been suggested that this may be due to differences in strategies used for learning by students with high (versus low) visuospatial abilities. Despite this, the degree of correlation between students’ approaches to learning and visuospatial abilities has yet to be investigated. The present study therefore aimed to examine the relationship between students’ approaches to learning, visuospatial abilities, and performance in anatomy to investigate the validity of the student approach to learning framework as an alternative metric to evaluate anatomy learning. Physical Therapy, Occupational Therapy, and Kinesiology students (n = 35) completed a Mental Rotations Test and Revised 2‐factor Study Process Questionnaire after the end of their first anatomy course. Responses and final course grades were examined using regression analyses to detect their degrees of correlation. We hypothesized that visuospatial ability would correlate positively with both anatomy performance and deep approach to learning scores and have a negative correlation with surface approach to learning scores. However, no significant correlations were found between visuospatial ability and deep or surface approach to learning scores at p ≤ 0.05. Anatomy performance was positively correlated with deep approach to learning scores ( β = 0.427, p = 0.02) and negatively correlated with surface approach to learning scores ( β = ‐0.704, p < 0.01) but had no significant correlation with visuospatial ability at p ≤ 0.05. The data suggest that visuospatial ability does not significantly influence students' approaches to learning; however, additional research on larger populations is required to explore these relationships further.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.488

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 integrity0.0000.001
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 head0.109
GPT teacher head0.327
Teacher spread0.218 · 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 teacher head, 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
Published2020
Admission routes1
Has abstractyes

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