Introducing diverse undergraduates to research during their undergraduate programs is an important for the educational enterprise supporting the STEM fields. The primary goal here is to provide the participants a taste of research with the auxiliary goal of some carryover to their skill set.
A key feature of modeling and computational representations and methods is that they cut across engineering disciplines and collectively offer a targeted introduction into the various application domains. This multidisciplinary characteristic offers students the opportunity to explore a wider set of problems than would be afforded by an experimental lab-based REU experience. Typically, REUs are run by research centers or large research operations under a few faculty researchers. However, there are a large number of faculty members in most institutions who have a modest level of research, unique abilities to introduce undergraduates to research, but for whom proposing and running an NSF REU site would involve a tremendous administrative workload. This REU site had researchers who are primarily senior and junior faculty with individual or small group research efforts, that can provide unique experiences for undergraduates. Third, due to the nature of computational research, the introduction and training of the participants in modeling tools can be addressed in common group sessions; however, research projects will be conducted with individual mentors.
The goals of the REU site, EMCoR@NCAT at North Carolina A&T State University (NCAT), was to provide summer research opportunities in the area of engineering modeling and computational research for qualified science, mathematics, and engineering undergraduates. EMCoR@NCAT participants worked under the mentorships of experienced researchers at NCAT and used established research laboratories in the College of Engineering. These goals were accomplished by:
1. Assembling a core faculty research group in engineering modeling and computational research.
2. Establishing a REU program that prepares participants for the target research areas, research training,
and professional development in a positive and rewarding scholarly climate.
3. Providing mentorship and guidance for research and professional preparation for graduate level
In addition to the above programmatic objectives, by the end of the research experience, the goal was to prepare the participants in the REU will be able to:
(a) demonstrate an understanding of the tools available for modeling and computational research;
(b) state and communicate a research problem and research goals in a domain, with the guidance of a
(c) plan and complete a research task with the guidance of a research mentor;
(d) demonstrate intellectual independence and creativity; and
(e) communicate the research problem, goals, plan, work, and results to diverse audiences.
Recruitment efforts targeted rising juniors and seniors who have strong mathematics and physics backgrounds. Some exposure to engineering coursework was desirable, but not required. Aptitude towards computational work evidenced by applicants’ transcripts was considered. A special focus was to recruit students enrolled in institutions, from the region that included North Carolina and the neighboring states, that may not have the resources to offer research experiences in these fields.
Following the orientations, the program will begin with 7.5 days of intensive instruction in computational modeling. The course involves fifteen half-day sessions, and will be taught in a computer lab. The following topics will be addressed: Engineering Modeling Methods, MATLAB Computing Software, and Computational Engineering Methods. At the end of each of the week, a research mentor will present on their current research, and provide an opportunity for discussion.
The final 2.5 days of the training session involved four components of computational thinking and tools of the trade. The computational thinking session includes constructing approximate finite precision solutions for mathematical equations governing the description of the real world, the mathematics of finite precision arithmetic for computational modeling, using the Linux operating system, research computing environments from the desktop to large scale computing and clusters, and scientific visualization.
After the participants complete the introductory course, they transition to the research intensive portion of the REU. Each participant will meet with their mentor to finalize their respective research project plans. Plans will be presented to the faculty mentor and research group in a seminar format on the first Friday of the second week. The participant will then spend the majority of the next seven weeks completing research activities with the faculty mentor. While the sequence of research activities and the meeting schedules will vary within each research group, there will be some meetings with mentors each week, one weekly research group meeting, and have daily office hours for research assistants. All mentors will emphasize positive interdependence within their research group, face-to-face interactions, individual accountability, skills for functioning in groups, professional skills as it relates to research, and collective discussion of the research of all students in the group. Course instructors will also be available to assist via email or by appointment.
An example research project entitled “Data-driven low-order modeling of propulsion systems in supersonic vehicles” was mentored by a faculty member in Mechanical Engineering. The MS and PhD students of the faculty member, working in a similar area, also serve as research mentors. After getting exposure to the application area, the participant id provided a topic statement such as: “conduct modeling with data sets already collected from the wind tunnel experiments where pressure is input and corresponding shock position is output. Develop first and second-order models, which are reasonably accurate but low order in order to be used in designing controllers.” For this project the research activities are as follows: “For the first research week, participants will begin with a thorough literature survey on data-based modeling and autonomous control using internet searching tools (e.g., Google Scholar) and visiting the library on campus with mentors. During the following week, students will be trained by the mentors on how to use MATLAB/Simulink focused on system identification and design of control. For the next two weeks, the students will be given data sets and modeling requirements. Using analytical and numerical methods participants will create differential equations that represent the dynamics and alidate the models using the skills learned in the previous stage. During the last 3.5 weeks, participants will design controllers and simulate it using MATLAB/Simulink based on the models they derived and control criteria.” At the of 10 weeks, the participants prepare a technical report on the experiences they have acquired. The report will clearly state the specific objectives of the research study and provide a global picture of the original research problem, will include a literature survey on the topic, research completed, and results.
The evaluation plan included a hypothesis of increased modeling self-efficacy from pre-test to post-test. Three focus groups were conducted during the summer for just-in-time (JIT) continuous improvement.
This paper presents the results from a three-year experience with leading a National Science Foundation-sponsored (grant number ACI-1560385) Research Experience for Undergraduates (REU) site: the recruitment, the diversity of each cohort, the projects, the activities, and the assessment results.
Are you a researcher? Would you like to cite this paper?
Visit the ASEE document repository at
for more tools and easy citations.