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Enhancing Student Success by Combining Pre-enrollment Risk Prediction with Academic Analytics Data

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Outreach, recruiting, and retention

Tagged Division

Biological & Agricultural

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Paper Authors


D. Raj Raman Iowa State University Orcid 16x16

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Raj Raman is Professor in the Agricultural and Biosystems Engineering (ABE) Department at Iowa State University, where he is also University Education Program Director and Testbed Champion for the NSF Engineering Research Center for Biorenewable Chemicals (CBiRC), Director of Graduate Education for the Interdepartmental Graduate Minor in Biorenewable Chemicals, and Education Programs Co-Leader for the USDA-AFRI project CenUSA Sustainable Production and Distribution of Biofuels for the Central USA. He is a licensed Professional Engineer who earned his BS in Electrical Engineering from the Rochester Institute of Technology and his PhD in Agricultural and Biological Engineering from Cornell University. Prior to coming to Iowa State in 2006, he was a faculty member at the University of Tennessee for over twelve years.

Raman enjoys teaching and has taught courses including freshmen engineering (mechanics and computer programming – to classes ranging in size from 20 to 500+), sophomore and junior level courses on mass and energy balance applications to biological systems engineering, numerical methods, electric power and electronics for technology students, senior design, as well as a long-standing residential/online graduate course on the fundamentals of biorenewable resources and technology. He has leveraged this interest into over $10M in teaching-related grant funding over his career and has contributed broadly to the literature in areas of curriculum, student risk characterization, and mentoring. He believes well trained, curious, thoughtful people are crucial to a university’s research effort, and similarly to the function and survival of society. For this reason, the overarching goal of his teaching is to impart the core content needed by the students, and to do so while encouraging inquisition and higher levels of thought. He has secured competitive funds to support his teaching efforts – from university, industry, and federal sources – and for his efforts has received departmental, college, and national teaching honors including the Farrall Young Educator Award (2004) and the Massey-Ferguson Gold Medal Teaching Award (2016) given by the American Society of Agricultural Engineers. He has also been an invited participant in the National Academy of Engineering’s 2013 Frontiers in Engineering Education Conference.

Raman chairs the ABE Engineering Curriculum Committee and in that role oversaw the successful 2012 ABET accreditation visit for both the Agricultural Engineering (AE) and Biological Systems Engineering (BSE) degree programs. Upon arriving at ISU in 2006, he led the development of the BSE program, and this program now enrolls over 100 students. Raman also runs multiple summer research internship programs through his roles in CBiRC and CenUSA – over 200 students have participated in summer programs he directed over the past decade. In his role as Pyrone Testbed Champion for CBiRC, Raman and his students have developed early-stage technoeconomic models of bioprocessing systems. His graduate students have gone on to faculty positions at peer institutions, and to engineering leadership positions at companies including Cargill, Nestle, and Merck.

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Amy L. Kaleita Iowa State University

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Amy L. Kaleita is Associate Professor of Agricultural and Biosystems Engineering at Iowa State University, and a licensed professional engineer. She has a B.S. in Agricultural Engineering from Penn State University, an M.S. in Civil and Environmental Engineering from the University of Illinois at Urbana-Champaign, from which she also has a PhD in Agricultural Engineering. Her disciplinary research is in the area of data mining and information technologies for precision soil and water conservation.

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For nearly a decade, our institution has used multiple-linear-regressions models to predict student success campus-wide. Over the past three years, we worked to refine the success prediction models to the college of engineering (COE) students in particular, and to explore the use of classification and regression tree (CART) approaches to doing the prediction (e.g., Authors, 2016). In a parallel effort, our institution has contracted with an academic analytics company to do a retrospective analysis of student performance in every course as the university in relation to graduation rates. Here, we report on recent work we have done to make synergistic use of the results from the COE CART model and the academic analytics. Specifically, we have been able to examine student performance (i.e., grades) in core “success marker” courses as a function of the risk-grouping into which the CART model places them. We are now using this information to inform our advising. We provide details on these efforts, and on the opportunities and challenges provided by data-driven approaches to enhancing student success.

Raman, D. R., & Kaleita, A. L. (2017, June), Enhancing Student Success by Combining Pre-enrollment Risk Prediction with Academic Analytics Data Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28281

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