Investigating users' requirements: computer-based anatomy learning modules for multiple user test beds.

Abstract

OBJECTIVE: User data and information about anatomy education were used to guide development of a learning environment that is efficient and effective. The research question focused on how to design instructional software suitable for the educational goals of different groups of users of the Visible Human data set. The ultimate goal of the study was to provide options for students and teachers to use different anatomy learning modules corresponding to key topics, for course work and professional training. DESIGN: The research used both qualitative and quantitative methods. It was driven by the belief that good instructional design must address learning context information and pedagogic content information. The data collection emphasized measurement of users' perspectives, experience, and demands in anatomy learning. MEASUREMENT: Users' requirements elicited from 12 focus groups were combined and rated by 11 researchers. Collective data were sorted and analyzed by use of multidimensional scaling and cluster analysis. RESULTS: A set of functions and features in high demand across all groups of users was suggested by the results. However, several subgroups of users shared distinct demands. The design of the learning modules will encompass both unified core components and user-specific applications. The design templates will allow sufficient flexibility for dynamic insertion of different learning applications for different users. CONCLUSION: This study describes how users' requirements, associated with users' learning experiences, were systematically collected and analyzed and then transformed into guidelines informing the iterative design of multiple learning modules. Information about learning challenges and processes was gathered to define essential anatomy teaching strategies. A prototype instrument to design and polish the Visible Human user interface system is currently being developed using ideas and feedback from users.