{"title":"The cognitive structure of gross anatomy knowledge in physiotherapy students.","authors":"Allan Besselink","doi":"10.1002/ase.2519","DOIUrl":null,"url":null,"abstract":"<p><p>Cognitive structures are the mental representation of domain knowledge and its organization. A preliminary investigation of the cognitive structure of gross anatomy knowledge was conducted on physiotherapy students. The criterion-related validation study examined two data modeling strategies (multidimensional scaling and Pathfinder networks) as potential visual and quantitative representations of cognitive structure. Two criterion standards were used: expert cognitive structure (concurrent) and the student's unit grade (predictive). The raw data for both data modeling strategies were generated from an online survey of paired comparisons of 20 anatomical structures and concepts relevant to musculoskeletal clinical practice. Convenience sampling was used to recruit first-semester physiotherapy students (n = 31), gross anatomy course instructors (n = 4), and domain experts (n = 3) who completed the online survey. The results indicated moderate-to-high effect sizes, regarding the level of agreement (reliability, accuracy, and association) between student and expert cognitive structures. Multiple regression analysis was performed to examine the potential relationships with unit grades. Six predictor variables accounted for 68.9% of the variance in unit grade, indicating a large effect size. The results provide preliminary evidence of concurrent and predictive criterion-related validity for using data modeling strategies to represent cognitive structure in this knowledge domain and population. Further research is indicated to assess the potential impact of this innovative use of data modeling strategies for cognitive structure mapping on gross anatomy education, adaptive learning, and competency-based education, leading to the long-term development of expertise.</p>","PeriodicalId":124,"journal":{"name":"Anatomical Sciences Education","volume":" ","pages":""},"PeriodicalIF":5.2000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anatomical Sciences Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1002/ase.2519","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: 0
Abstract
Cognitive structures are the mental representation of domain knowledge and its organization. A preliminary investigation of the cognitive structure of gross anatomy knowledge was conducted on physiotherapy students. The criterion-related validation study examined two data modeling strategies (multidimensional scaling and Pathfinder networks) as potential visual and quantitative representations of cognitive structure. Two criterion standards were used: expert cognitive structure (concurrent) and the student's unit grade (predictive). The raw data for both data modeling strategies were generated from an online survey of paired comparisons of 20 anatomical structures and concepts relevant to musculoskeletal clinical practice. Convenience sampling was used to recruit first-semester physiotherapy students (n = 31), gross anatomy course instructors (n = 4), and domain experts (n = 3) who completed the online survey. The results indicated moderate-to-high effect sizes, regarding the level of agreement (reliability, accuracy, and association) between student and expert cognitive structures. Multiple regression analysis was performed to examine the potential relationships with unit grades. Six predictor variables accounted for 68.9% of the variance in unit grade, indicating a large effect size. The results provide preliminary evidence of concurrent and predictive criterion-related validity for using data modeling strategies to represent cognitive structure in this knowledge domain and population. Further research is indicated to assess the potential impact of this innovative use of data modeling strategies for cognitive structure mapping on gross anatomy education, adaptive learning, and competency-based education, leading to the long-term development of expertise.
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.