with a joint appointment in the Department of Bioengineering. Dr. Benson teaches first year engineering, research methods, and graduate engineering education courses. Her research interests include student-centered active learning in undergraduate engineering, assessment of motivation, and how motivation affects student learning. She is also involved in projects that utilize Tablet PCs to enhance student learning. Her education includes a B.S. in Bioengineering from the University of Vermont, and M.S. and Ph.D. degrees in Bioengineering from Clemson University.

It is estimated that students now graduating will pursue as many as five careers in their lifetime. This puts increasing pressure on instruction to expedite a student's ability to transfer what they have learned in the classroom to many applications. Many times the learning experiences students have in the classroom become isolated and limited because of the lack of context in which the learning experience occurs. With this in mind, a Movement Science in Biomechanics course was designed to enhance learning experiences by tying the course objectives to the context of clinical applications. According to situated cognition theory, students learn best by doing what experts in that field are doing. Activities were designed based on the typical activities in a motion and gait laboratory including kinematic analysis using inertial sensors and goniometers, kinetic analysis using a force plate, and muscle activity using electromyography technology. Each activity was introduced as a goal-based scenario in which the groups constructed the necessary knowledge needed to solve a problem in their own way and justified their solution through a report and/or presentation. Scenarios included characterization and optimization of a golf swing, ground forces associated with an ACL tear, and muscle recruitment and activity during cycling. Problem scaffolding based on constructivist theory was necessary to develop the skills and schema to solve the scenarios without cognitive overload. To do this, students were divided into subgroups in which they became "experts" with one of the skill sets and technologies. Collaborative groups were then comprised of several different "experts" that worked together to solve the goal-based scenario. Dependence on each of the group member's expert skills encouraged individual accountability within the group. The groups pursued a research question of their own for their final project which was based on multiple technologies and skills sets learned throughout the class. Students' pre-and post-test performance on statics and force concept inventories were compared. Perceptions of learning gains and expert experience were assessed through student interviews and surveys. We will report on these results and discuss implications and limitations on learning through constructed contextual knowledge based on situated cognition and constructivist theory.