Visuospatial Ability and Student Approach to Learning as Predictors of Academic Performance on Written versus Laboratory-Based Assessments in Human Anatomy

Autor/inn/en	Wang, Catherine; McWatt, Sean C.
Titel	Visuospatial Ability and Student Approach to Learning as Predictors of Academic Performance on Written versus Laboratory-Based Assessments in Human Anatomy
Quelle	In: Anatomical Sciences Education, 16 (2023) 6, S.1187-1199 (13 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Wang, Catherine) ORCID (McWatt, Sean C.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1935-9772
DOI	10.1002/ase.2317
Schlagwörter	Visual Perception; Spatial Ability; Human Body; Anatomy; Learning Processes; Predictor Variables; Academic Achievement; Student Evaluation; Evaluation Methods; Science Laboratories; Grades (Scholastic); Electronic Learning + Suchen Sie Ihr Suchwort? Visuelle Wahrnehmung; Räumliches Vorstellungsvermögen; Menschlicher Körper; Anatomie; Learning process; Lernprozess; Prädiktor; Schulleistung; Schulnote; Studentische Bewertung; Notenspiegel
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. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01