2023 ASEE Annual Conference & Exposition

Jigsaws are an active-learning method which expedites learning, collaborative problem-solving and teamwork skills development. Jigsaws have been used effectively in classrooms ranging from K-12 to advanced engineering courses. A Jigsaw is a team-of-teams activity in which students work in an expert group to develop competence on a topic. Each expert group studies a different topic in depth. Then, as jigsaw teams—comprised of a member from each expert group—students work collaboratively to teach each other what they have learned as they put together and map out the complete activity. Jigsaws tend to foster interdependence and individual accountability.

This paper focuses on evaluation of a jigsaw activity conducted in Medical Informatics and Telemedicine, an elective course for Junior and Senior level biomedical engineering students at Wentworth Institute. The course is not theoretical but focused on applications, delivered in the form of lectures, labs, and workshops, where students, individually and in groups, learn about and explore different aspects of health informatics systems and process design. Active learning interventions used in the course build off real-world scenarios such as design of electronic health record systems (EHR), implementation of clinical decision support rules, evaluation of system interoperability, and health information exchanges. Students analyze the scenarios by creating “end-to-end” diagrams and maps of the “patient and data journeys.”
A fictional but realistic scenario, adapted from the cornerstone Shortliffe textbook, in which a diabetic patient’s progression along the continuum of care is used to illustrate the design and operation of an EHR. Jigsaws are an ideal method for analyzing clinical processes and workflows, such as EHR systems. Divided into jigsaw teams, students collaboratively map out the workflows, analyze software modules and features, and evaluate interoperability, clinical-decision-support, telehealth consultations, and clinical outcomes.
Preliminary data analysis of student responses to end of semester course evaluations seems to indicate that jigsaws can be an effective active learning intervention which bolsters analytical and collaboration skills in courses involving systems and process design. The next stage of analysis would include coding more data sets and addition of other methods, such as a photovoice protocol to analyze students’ graphical reports and documents collected.