Closing the Loop: A 10-year Follow-up Survey for Evaluation of an NSF REU Site

Yufang Jin; Chunjiang Qian; Sara Ahmed

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Conference: 2022 ASEE Annual Conference & Exposition
Location: Minneapolis, MN
Publication Date: August 23, 2022
Start Date: June 26, 2022
End Date: June 29, 2022
Conference Session: ECE Division Technical Session 2: Long-Term Institutional Outcome Evaluations and Capstone Innovations
Page Count: 13
DOI: 10.18260/1-2--41048
Permanent URL: https://peer.asee.org/41048
Download Count: 484

Paper Authors

biography

Yufang Jin The University of Texas at San Antonio

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Dr. Jin is a full professor with the Department of Electrical and Computer Engineering at the University of Texas at San Antonio. Her research interest focuses on modeling and control of nonlinear systems, applications of deep learning algorithms to biological systems, and pedagogy in Engineering Education.

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biography

Chunjiang Qian The University of Texas at San Antonio

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Dr. Chunjiang Qian received his Ph.D. degree in Electrical Engineering from Case Western Reserve University, 2001. Since August 2001, he has been with the Department of Electrical and Computer Engineering, University of Texas at San Antonio, where he is currently the department chair and Mary Lou Clarke Endowed Professor.

His current research interests include robust and adaptive control, nonlinear system theory, optimal control, network control, and mathematical foundation of deep learning. He has also applied research to UAV systems, power generation systems, electric vehicles, and marine vehicles.

Dr. Qian is a recipient of 2003 U.S. National Science Foundation (NSF) CAREER Award and one of the inaugural recipients of the University of Texas System Regents’ Outstanding Teaching Award in 2009. He received the 3rd Best Paper Award in the ISA (International Society of Automation) Power Industry Division Symposium (2011) and the Best Poster Paper Award in the 3rd IFAC International Conference on Intelligent Control and Automation Science (2013). He currently serves as an Associate Editor for Automatica and International Journal of Robust and Nonlinear Control. Dr. Qian is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE).

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Sara Ahmed The University of Texas at San Antonio

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Dr. Sara Ahmed is an Assistant Professor in the Electrical & Computer Engineering Department in the University of Texas at San Antonio. She received her Bachelor’s, Master’s and Ph.D. degrees all in Electrical Engineering with a Power Electronics concentration from Virginia Tech, Center for Power Electronics in 2006, 2007, and 2011 respectively. Dr. Ahmed has five years of prior R&D industry experience as a Senior Scientist at ABB’s U.S Corporate Research Center in Raleigh, NC. Her primary research interests are in the area of modeling, simulation and analysis of power electronics systems with a focus on control, stability, fault analysis, model prediction, integration of renewables and hardware-in-the-loop modeling and testing. She holds eight granted U.S. patents, 2 U.S. patent applications and more than 45 referred publications.

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Abstract

Objective and Motivation: Research Experience for Undergraduates (REU) has been a very effective way to foster students’ interest in research, attract more students to pursue advanced degrees in Science, Technology, Engineering, and Mathematics (STEM), and promote a well-trained diverse workforce in the future. Most evaluations of REU programs focus on current progress and outcomes in a near future. However, most REU trainees are juniors and the post-graduate education programs for advanced degrees, especially Ph.D. training, can easily span from 3 to 5 years, leading to a much longer period than the funding period of REU programs. With this consideration, the final report on REU programs can not include the complete outcomes of REU programs. The goal of this project is to establish a closed-loop evaluation structure for identifying significant factors to promote undergraduate students in the engineering career path, and integrating the experiences learned from the previous REU program into an ongoing REU program.

Methods: We executed a survey for 26 former REU trainees who were trained 10 years ago. Questions in the survey for former REU trainees include when and where they earned their highest academic degree, GPA at graduation, a career path in academic or industrial sectors, careers in STEM or not, regions of current locations, trainees-advisor interactions using email/social media, and REU trainees’ follow-up evaluation of the REU site. Among all 26 former REU trainees, 11 got a master’s degree or doctoral degree in either Computer Science or Electrical and Computer Engineering. Further, 3 out of 7 trainees who got Ph.D. degrees chose an academic career path in their trained research area at the REU site.

Assessment Methods: REU trainees’ demographics, first-generation student or not, career achievement, and evaluations of the REU site were analyzed by an evaluation model associated with their final degree outcomes, academic GPA, number of publications during the REU training, and frequency of interactions among faculty members and the REU trainees during and post the REU training.

Statement of Results: This is the first longitudinal study on an assessment of the benefits of REU in Electrical and Computer Engineering. This study provides insight into the role of research experiences prior to graduate school in the transition of REU trainees into their professional career development. The findings strongly support that engagement of REU trainees provides thrust in their transition to graduate schools. Specifically, joint publications, interaction strength with their REU mentors post-REU training, and professional community activities are the top three contributing factors to the engagement.

Citation
Format

Jin, Y., & Qian, C., & Ahmed, S. (2022, August), Closing the Loop: A 10-year Follow-up Survey for Evaluation of an NSF REU Site Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41048

TY - CPAPER
AB - Objective and Motivation: Research Experience for Undergraduates (REU) has been a very effective way to foster students’ interest in research, attract more students to pursue advanced degrees in Science, Technology, Engineering, and Mathematics (STEM), and promote a well-trained diverse workforce in the future. Most evaluations of REU programs focus on current progress and outcomes in a near future. However, most REU trainees are juniors and the post-graduate education programs for advanced degrees, especially Ph.D. training, can easily span from 3 to 5 years, leading to a much longer period than the funding period of REU programs. With this consideration, the final report on REU programs can not include the complete outcomes of REU programs. The goal of this project is to establish a closed-loop evaluation structure for identifying significant factors to promote undergraduate students in the engineering career path, and integrating the experiences learned from the previous REU program into an ongoing REU program.

Methods: We executed a survey for 26 former REU trainees who were trained 10 years ago. Questions in the survey for former REU trainees include when and where they earned their highest academic degree, GPA at graduation, a career path in academic or industrial sectors, careers in STEM or not, regions of current locations, trainees-advisor interactions using email/social media, and REU trainees’ follow-up evaluation of the REU site. Among all 26 former REU trainees, 11 got a master’s degree or doctoral degree in either Computer Science or Electrical and Computer Engineering. Further, 3 out of 7 trainees who got Ph.D. degrees chose an academic career path in their trained research area at the REU site.

Assessment Methods: REU trainees’ demographics, first-generation student or not, career achievement, and evaluations of the REU site were analyzed by an evaluation model associated with their final degree outcomes, academic GPA, number of publications during the REU training, and frequency of interactions among faculty members and the REU trainees during and post the REU training.

Statement of Results: This is the first longitudinal study on an assessment of the benefits of REU in Electrical and Computer Engineering. This study provides insight into the role of research experiences prior to graduate school in the transition of REU trainees into their professional career development. The findings strongly support that engagement of REU trainees provides thrust in their transition to graduate schools. Specifically, joint publications, interaction strength with their REU mentors post-REU training, and professional community activities are the top three contributing factors to the engagement.

AU - Yufang Jin
AU - Chunjiang Qian
AU - Sara Ahmed
CY - Minneapolis, MN
DA - 2022/08/23
PB - ASEE Conferences
TI - Closing the Loop: A 10-year Follow-up Survey for Evaluation of an NSF REU Site
UR - https://peer.asee.org/41048
DO - 10.18260/1-2--41048
ER -