This grant to Purdue University seeks two years of NSF funding to develop a novel and systematic approach to better understand the direct and indirect relationships among freshman engineering student attributes and outcomes. With this knowledge, the college will implement processes that: a) enable faculty and advisors to give more informed guidance to incoming freshmen about their course selections; b) foster the continuous improvement of first-year engineering experiences; c) provide a means to operationalize the definition of student success to include additional features (i.e., something more than simply looking at GPA and persistence in engineering); and d) facilitate our ability to investigate differences in a model of predictors and outcomes for underrepresented student groups (e.g., gender, and ethnicity), leading to more meaningful advising for these students.
This project will develop a comprehensive evaluation process that will enable engineering faculty and advisors to better assess: the cognitive and noncognitive characteristics of incoming freshman to more accurately place students into the most appropriate introductory chemistry, engineering, mathematics, and physics courses. In addition, the project to use survey items (self-concepts and expectations), prior academic performance (high school academic record), and student assessment of their achievement to understand the direct and indirect relationships among freshman student attributes and outcomes in order to provide the foundation for continuous improvement in our first-year engineering program, as well as provide a bases by which we can measure whether a student has had a successful first-year experience.
The current model for engineering accreditation calls for the development and implementation of a system of ongoing evaluation that demonstrates achievement of programs educational objectives, in part, through the assessment of program outcomes. However, to date, no effort has been made to relate these outcomes back to a student's starting point in the higher education system. We believe the model proposed herein will serve in that capacity both at Purdue University and engineering institutions across the country.
