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Characterizing the Complexity of Curricular Patterns in Engineering Programs

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Understanding the Discipline of Engineering

Tagged Division

Educational Research and Methods

Page Count

12

DOI

10.18260/1-2--28029

Permanent URL

https://peer.asee.org/28029

Download Count

520

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Paper Authors

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Gregory L. Heileman University of New Mexico Orcid 16x16 orcid.org/0000-0002-5221-5682

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Gregory (Greg) L. Heileman serves as the Vice Provost for Teaching and Learning at the University of New Mexico (UNM). From 2011 until 2016, he served as the Associate Provost for Curriculum at UNM. During that time he led campus-wide student academic success initiatives, and worked with key stakeholders on campus, to produce all-time record retention and graduation rates. In 1990 he joined the Department of Electrical and Computer Engineering (ECE) at the University of New Mexico, Albuquerque, NM, where he is currently a Professor. From 2005-2011 he served as Associate Chair (Director of Undergraduate Programs), and led the department through two ABET accreditation visits. In 2011 he became an ABET program evaluator. In 2009 he was also awarded the IEEE Albuquerque Section Outstanding Educator Award. He was the recipient of ECE’s Lawton-Ellis Award for combined excellence in teaching, research, and student/community involvement in 2001 and again 2009. He held ECE’s Gardner Zemke Professorship from 2005-08. He received the School of Engineering's Teaching Excellence award in 1995, and the ECE Department Distinguished Teacher Award in 2000. During 1998 he held a research fellowship at the Universidad Carlos III de Madrid, and in 2005 he held a similar position at the Universidad Politénica de Madrid. He earned the BA degree from Wake Forest University in 1982, the MS degree in Biomedical Engineering and Mathematics from the University of North Carolina-Chapel Hill in 1986, and the PhD degree in Computer Engineering from the University of Central Florida in 1989.

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Michael Hickman

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Michael Hickman received his BS in Computer Engineering from the University of New Mexico in 2014 and is now pursing his MS degree. He is currently working for UNM's Institute of Design & Innovation to provide the University with tools and analytics that can aid in improving student success.

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Ahmad Slim

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Chaouki T. Abdallah University of New Mexico

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Chaouki T. Abdallah started his college education at the Ecole Supérieure d'Ingénieurs de Beyrouth - Université Saint-Joseph in Beirut, Lebanon, but finished his undergraduate studies at Youngstown State University, with a Bachelors of Engineering degree in Electrical Engineering in 1981. He then obtained his MS and Ph.D. in Electrical Engineering from GA Tech in 1982, and 1988 respectively. He joined the Electrical and Computer Engineering department at the University of New Mexico where he is currently professor and since 2011, the provost & EVP for academic affairs, and acting president since January 2017. Professor Abdallah conducts research and teaches courses in the general area of systems theory with focus on control and communications systems. His research has been funded by national funding agencies, national laboratories, and by various companies. He has also been active in designing and implementing various international graduate programs with Latin American and European countries. He was a co-founder in 1990 of the ISTEC consortium, which currently includes more than 150 universities in the US, Spain, and Latin America. He has published 7 books, and more than 300 peer- reviewed papers. His PhD students hold academic positions in the USA and in Europe, and senior technical positions in various US National Laboratories.

Professor Abdallah is a senior member of IEEE and a recipient of the IEEE Millennium medal. He is also active in the IEEE Control Systems Society most recently serving as the general chair of the 2008 Conference of Decision and Control CDC 2008.

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Abstract

Engineering programs tend to follow common patterns for educating undergraduate stu- dents through the sophomore year. For instance, a portion of a common curricular pattern for electrical engineering involves the sequence: Calculus I –> Calculus II –> Differential Equations –> Circuits I. In mechanical engineering programs the common curricular pattern includes the sequence: Calculus I –> Calculus II –> Differential Equations –> Mechanics. The curricular patterns themselves are more complicated than these sequences, often involving additional pre- and co-requisite courses that must be passed in order for a student to progress through the curriculum. These patterns may be modeled as directed graphs, and the complexity of the pattern can then be characterized according to the delay and blocking factors present in the graphs. The key point is that failure to pass a course that occurs earlier in a curricular pattern, or the inability to start the pattern on schedule (e.g., due to math placement issues) will often necessitate a delay in graduation. Because these engineering curricular patterns are complex, they tend to produce a longer time-to-degree than other disciplines.

A number of schools have implemented engineering curricular reforms that are aimed at improving on-time graduation rates. These generally involve modifying the patterns described above in some way that is meant to improve student success. In this paper we apply curricular analytics techniques to these patterns in order to quantify the extent to which particular reforms should improve graduate rates. Our work involves breaking curricular complexity into two components: (1) the structural complexity, which is determined by the manner in which the courses in a curriculum are organized, e.g., prerequisites, number of courses, etc., and (2) the instructional complexity, which is determined by the inherent difficulty of the courses in the curriculum, the quality of the faculty and academic support, etc. We then demonstrate how these measures can be used within a simulation environment to estimate the impact that particular curricular improvements will have on student outcomes. This will reveal that many engineering curricula have highly “sensitive” course patterns (and in some cases individual courses) that will yield large increases in graduation rates for small improvements in course success rates. Finally, we demonstrate how curricular analytics can be used to compare the complexities of similar programs at different institutions, as well as how these tools can be used to guide faculty discussions around curricular reform.

Heileman, G. L., & Hickman, M., & Slim, A., & Abdallah, C. T. (2017, June), Characterizing the Complexity of Curricular Patterns in Engineering Programs Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28029

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