Assessing the Impact of an REU Program on Students’ Intellectual Growth and Interest in Graduate School in Cybermanufacturing

Abstract

Advancements in information technology and computational intelligence have transformed the manufacturing landscape, allowing firms to produce highly complex and customized product in a relatively short amount of time. However, our research shows that the lack of a skilled workforce remains a challenge in the manufacturing industry. To that end, providing research experience to undergraduates has been widely reported as a very effective approach to attract students to industry or graduate education in engineering and other STEM-based majors. This paper presents assessment results of two cohorts of Cybermanufacturing REU at a major university. Students were recruited from across the United States majoring in multiple engineering fields, such as industrial engineering, mechanical engineering, chemical engineering, mechatronics, manufacturing, and computer science. Several of the participants were rising sophomores or juniors who did not have any industry internship or prior research experience. In total 20 students (ten per year) participated in the program and worked on individual project topics under the guidance of faculty and graduate student mentors. Unlike a typical REU program, the Cybermanufacturing REU involved a few unique activities, such as a 48-hour intense design and prototype build experience (also known as Aggies Invent), industry seminars, and industry visits. Overall, the REU students demonstrated significant gains in all of the twelve research-related competencies that were assessed as a part of formative and summative evaluation process. While almost all of them wanted to pursue a career in advanced manufacturing, including Cybermanufacturing, the majority of the participants preferred industry over graduate school. The paper provides an in-depth discussion on the findings of the REU program evaluation and its impact on undergraduate students with respect to their future plans and career choice. The analysis is also done by gender, ethnicity, academic level (sophomore, junior, senior), and type of home institution (e.g., large research universities, rural and small schools) to explore if there was any significant difference in mean research competency scores based on these attributes.