Visuospatial ability and student approach to learning as predictors of academic performance on written versus laboratory-based assessments in human anatomy
{"title":"Visuospatial ability and student approach to learning as predictors of academic performance on written versus laboratory-based assessments in human anatomy","authors":"Catherine Wang, Sean C. McWatt","doi":"10.1002/ase.2317","DOIUrl":null,"url":null,"abstract":"As hours devoted to human anatomy curricula fall under threat and curricular delivery methods remain in flux, many new teaching innovations are emerging, which require comprehensive evaluation to ensure evidence‐based teaching is maintained. Although grades are the predominant measure of ‘learning’, alternative metrics can assess more nuanced and meaningful outcomes. Two common predictors of students' three‐dimensional understanding of the body and depth of learning are visuospatial abilities and approaches to learning, respectively. This study evaluated and compared the relative predictive power of these metrics on written and laboratory‐based assessments in a human anatomy course. Deep approaches to learning and visuospatial abilities were expected to positively correlate with overall performance, with visuospatial abilities being the more salient predictor, especially on laboratory‐based assessments. Additionally, visuospatial abilities were expected to positively correlate with deep learning approaches and negatively correlate with surface learning approaches. Multiple linear regression models controlling for covariates found that both visuospatial abilities (p = 0.049; p = 0.014) and deep learning approaches (p = 0.001; p = 0.001) were independent significant predictors of final and laboratory‐based grades, while only deep learning approaches were significantly predictive of written grades (p = 0.007). There was no significant relationship between visuospatial abilities and approaches to learning. Given these findings and the increased reliance on visuospatially demanding digital learning activities in anatomy, both metrics should be considered when evaluating the impact of teaching innovations. Further, educators should design learning resources and environments that train visuospatial abilities and promote deeper learning approaches to maximize students' success.","PeriodicalId":124,"journal":{"name":"Anatomical Sciences Education","volume":"16 6","pages":"1187-1199"},"PeriodicalIF":5.2000,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anatomical Sciences Education","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ase.2317","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 1
Abstract
As hours devoted to human anatomy curricula fall under threat and curricular delivery methods remain in flux, many new teaching innovations are emerging, which require comprehensive evaluation to ensure evidence‐based teaching is maintained. Although grades are the predominant measure of ‘learning’, alternative metrics can assess more nuanced and meaningful outcomes. Two common predictors of students' three‐dimensional understanding of the body and depth of learning are visuospatial abilities and approaches to learning, respectively. This study evaluated and compared the relative predictive power of these metrics on written and laboratory‐based assessments in a human anatomy course. Deep approaches to learning and visuospatial abilities were expected to positively correlate with overall performance, with visuospatial abilities being the more salient predictor, especially on laboratory‐based assessments. Additionally, visuospatial abilities were expected to positively correlate with deep learning approaches and negatively correlate with surface learning approaches. Multiple linear regression models controlling for covariates found that both visuospatial abilities (p = 0.049; p = 0.014) and deep learning approaches (p = 0.001; p = 0.001) were independent significant predictors of final and laboratory‐based grades, while only deep learning approaches were significantly predictive of written grades (p = 0.007). There was no significant relationship between visuospatial abilities and approaches to learning. Given these findings and the increased reliance on visuospatially demanding digital learning activities in anatomy, both metrics should be considered when evaluating the impact of teaching innovations. Further, educators should design learning resources and environments that train visuospatial abilities and promote deeper learning approaches to maximize students' success.
期刊介绍:
Anatomical Sciences Education, affiliated with the American Association for Anatomy, serves as an international platform for sharing ideas, innovations, and research related to education in anatomical sciences. Covering gross anatomy, embryology, histology, and neurosciences, the journal addresses education at various levels, including undergraduate, graduate, post-graduate, allied health, medical (both allopathic and osteopathic), and dental. It fosters collaboration and discussion in the field of anatomical sciences education.