MétaCan
Menu
Back to cohort

The Influence of Spatial Ability on Medical Student Performance in the Basic Sciences

2016· article· en· W4389024311 on OpenAlexaff
A. MURAT WILLIS, Anna Edmondson, Charys M. Martin

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsWestern University
Fundersnot available
KeywordsCurriculumTest (biology)Head and neckPhysiologyPsychologyAnatomyMedical educationMedical physicsMedicineNeuroscienceMathematics educationBiologySurgeryPedagogyEcology

Abstract

fetched live from OpenAlex

Background Spatial visualization ability (Vz) is associated with higher performance in anatomy; however, the influence of Vz on performance in the other basic sciences has not been established. This study aimed to assess the influence of Vz on academic performance in the first year basic science curriculum at the Medical College of Georgia. We hypothesized that students’ Vz will have a significant positive correlation with their performance in structural science components (anatomy, embryology, histology, and neuroscience) and the systems‐based modules focusing on structural science. Methods First year medical students (n=83) in a systems‐based integrated curriculum completed the Mental Rotations Test (MRT) at the beginning of the year prior to the start of anatomy to establish Vz (pre‐Vz). Students completed the MRT again at the end of the year to reassess Vz (post‐Vz). Academic performance was assessed via grades in each basic science component (anatomy, biochemistry, embryology, histology, neuroscience, and physiology) and systems‐based module (Cellular and Molecular Basis of Medicine, Tissue and Musculoskeletal System, Cardiopulmonary System, Gastrointestinal and Urinary Systems, Endocrine‐Reproductive Systems, Head and Neck and Special Senses, and Medical Neuroscience). Results A two‐tailed T‐test determined that there was a significant difference between pre‐Vz and post‐Vz (12.9±4.72; 16.0±4.85 respectively, p≤0.05). ANCOVA analysis demonstrated significant positive correlations between pre‐Vz and performance in histology (r 2 =0.117), the Cardiopulmonary module (r 2 =0.114), and the Head and Neck and Special Senses module ((r 2 =0.092), p=<0.05). Significant positive correlations were found between post‐Vz and performance in anatomy (r 2 =0.106), histology (r 2 =0.130), neuroscience (r 2 =0.114), physiology (r 2 =0.095), the Tissue and Musculoskeletal System module (r 2 =0.086), the Cardiopulmonary module (r 2 =0.131), the Gastrointestinal and Urinary module (r 2 =0.094), the Head and Neck and Special Senses module (r 2 =0.158), and the Medical Neuroscience module ((r 2 =0.050), p≤0.05). Conclusions In summary, performance in one component and two modules were positively correlated with pre‐Vz scores while performance in four components and five modules were positively correlated with post‐Vz scores. These results suggest that acquired Vz, as opposed to Vz at the beginning of the year, is associated with improved performance in the basic sciences within the first year medical curriculum. This indicates that training medical students to improve their Vz may be beneficial for medical school performance. Future studies are required to assess how Vz changes throughout the first year curriculum to determine how a change in Vz correlates with student performance within the basic sciences.

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)0.003
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 score0.903
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicAnatomy and Medical TechnologyFrench-language works237,207