An evidence-based intervention system is proposed to provide for guided evolution of engineering education programs. Too often, innovative designs for educational enhancement fall into disrepair because they embodied the unintended consequence of built-in obsolescence. The ineffectiveness of many designs has been resident in a static view of learning and teaching styles, personnel-dependence, an inability to manage changes in program size, and/or a lack of portability and adoption by the larger educational community. To avoid these specific pitfalls in our design for educational enhancement, we are: (1) employing a dynamic view of learning and teaching styles where the characteristics of student and faculty are periodically measured to establish an assessment process calibration, (2) using knowledge management systems to process voluminous data collection and analysis in an efficient and flexible manner, (3) using a modular design of an established assessment paradigm that provides points of real-time intervention to responsively optimize educational practices, and (4) using a widely-practiced assessment paradigm that confers transferability of the process with its value-added, best-practices modifications to other educational systems. The approach to accomplish these goals is based upon decision support software currently in use in business and health care. The implementation of Instructional Decision Support System (IDSS) approaches will provide rapid feedback of assessment data combined with student characteristics to empower faculty instructors and enhance student learning. Preliminary data has provided a basic proof-of-concept for the IDSS approach. Data from the Index of Learning Styles indicated that the students surveyed were sequential, as opposed to global, learners. Instructors found that redesigning some courses to provide a more sequential, step-by-step style enhanced the student experience in selected courses. Other data showed that students surveyed were not as positively inclined towards engineering as might be expected for a biomedical engineering program. If confirmed, this data can be used to provide support for developing new educational experiences targeted to improve students' attitudes towards the discipline.
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