Chemical Engineering 5743, “Chemical Engineering Modeling,” traditionally has been taught in the lecture format. The author has taught the course as such for seven years. In the fall of 2005, the co-author developed EXCEL/VBA demonstrations, activities, and homework, and the author did the same with MATLAB. These computer tools were used by the students to solve algebraic, ordinary differential equations (initial value and boundary value) and partial differential equations (parabolic and elliptic). Traditional courses will focus on numerical and mathematical methods as necessary skills. In the fall of 2006, the authors decided to add new components to the course exposing students to case studies, problem based learning, team work, and experimentation with the aim of promoting creative and critical thinking as students identify and practice the art of modeling.

The 13 students in the fall 2006 course were tasked with a semester project to “Design an encapsulated drug (of your group's choice) that effectively delivers an appropriate dose for an appropriate number of hours. Select the most cost effective method.” The students were introduced to the problem with a case study described in “User's Guide to Engineering” by Jensen, a freshman introductory engineering text. This “Dissolution Case Study” has been developed based on a series of several Chemical Engineering Education articles. In the case study, a lollipop simulates the coating of a new pharmaceutical. A simple first order ODE describes the rate of change of the lollipop radius with respect to time. This rate is dependent on the mass transfer coefficient, the concentration gradient, and the molar density of the lollipop. The case study then tasks the freshman students to develop experimental procedures to test the proposed model.

For the graduate course, the students were put in heterogeneous groups by considering their country of origin, the degree they are pursuing (M.S., Ph.D.), and their background experience in computer applications / programming, experimentation / lab work, and numerical method experience. The graduate students began by creating an initial experimental protocol for their physical model (equipment/supplies needed, data collection procedure), their initial computer modeling/numerical methods appropriate for solving the mathematical model, necessary simplifications made to begin the research, and expectations of future considerations that more appropriately model the real system. Throughout the semester the students improved their physical and mathematical modeling complexity to reach the goal of encapsulated drug design. Teams gave final presentations of the results of their efforts.

Assessments are presented examining the effectiveness of our team-based, active learning experience. Modeling, experimental design, experimental procedure and competence, and proficiency in applied numerical methods and computer programming are evaluated. This project proved invaluable for beginning graduate students to identify the connection between modeling, mathematical descriptions and experimental reality. It was also intriguing for the students to not only consider mathematical but physical models where experimentation with the real system is, at best impractical, as is the case in biological systems. The students gained valuable teamwork skills not common for many graduate students as well as gained improvements in communication skills.