2017 ASEE Annual Conference & Exposition

Board # 84 : Traditional versus Hardware-driven Introductory Programming Courses: a Comparison of Student Identity, Efficacy and Success

Presented at NSF Grantees Poster Session

For the past few years we have offered two versions of our introductory C programming course. The first is a traditional course where students are given individual paper-based programming assignments that do not involve any hardware besides the computer itself and its peripheral devices. In the other course, students do have some individual programming assignments, but there is a lab that involves mostly partner-based programming assignments emphasizing computer-controlled hardware-driven projects and a final multi-week group project. The Raspberry Pi (RPi) 3B computer is currently the device the students use for the hardware-based assignments, though there are many devices off the shelf today that have similar capabilities. Both classes use the same textbook. While the traditional course is two credits, the novel course is three credits to allow time for the hardware instruction. Students from both classes then need to take the same advanced C programming course that is also traditional in its format.

The novel course has been taught a total of four times for a total enrollment of about 80 students. This number has been limited by resources, as we have provided RPi kits for students and all necessary hardware from an NSF grant. The lecture has had at most 30 students and the once-weekly, three-hour computer labs have had at most 10 students. In contrast, the traditional course enrolls at least 90 students per year in two or three sections. The maximum lecture size is around 60 students and their hands-on, bi-weekly, hour-long discussion sessions are limited to 12 students.

We have been using mixed research methods, including student surveys, classroom observation, and student interviews, to compare the impact of these courses on student beliefs about programming, the electrical engineering profession, and their own abilities. The surveys have concentrated on pre-course and post-course identity and efficacy beliefs of the students. Preliminary findings [1] suggest that students in the novel course find their course more collaborative and more like “real-world” engineering than students in the traditional course did. Students in the novel course also had greater self-efficacy and identity gains, particularly regarding fitness as an engineer, as compared to students in the traditional course.

In this paper we will describe and discuss the results of our studies regarding student identity and efficacy beliefs from the two introductory courses for the totality of the NSF contract. We also detail the differences in the content and pedagogy of the traditional and novel courses and we will describe observations of student interactions in the two courses. We will present success rates for both cohorts of students in the advanced C programming course and look at the impact on students from underserved populations. Finally, we will discuss plans to develop a version of the advanced programming class that is hardware-driven.

[1] Authors, 2016

Authors

Prof. Wesley G. Lawson University of Maryland, College Park [biography]

Prof. Lawson has earned five degrees from the University of Maryland, including a Ph,D, in Electrical Engineering in 1985. In his professional career at College Park, where he has been a full professor since 1997, he has worked on high-power microwave de
Dr. Stephen Secules http://orcid.org/0000-0002-3149-2306 Florida International University [biography]

Dr. Stephen Secules is an Assistant Professor in the School of Universal Computing, Construction, and Engineering Education at Florida International University. Secules holds a joint appointment in the STEM Transformation Institute and a secondary appointment in the Department of Mechanical and Materials Engineering. He has bachelor degrees in engineering from Dartmouth College, a master’s in Architectural Acoustics from Rensselaer Polytechnic Institute, and a PhD in Education (Curriculum and Instruction) from the University of Maryland. Prior to his academic career, Stephen was an acoustical consultant for 5 years in both London, UK and Silicon Valley, CA. His research has focused on culture and equity in engineering education, particularly undergraduate contexts, pedagogy, and student support. Through his work he aims to use critical qualitative, video-based, participatory, and ethnographic methods to look at everyday educational settings in engineering and shift them towards equity and inclusion. He also leads the Equity Research Group where he mentors graduate and undergraduate students in pursuing critical and action-oriented research.
Prof. Shuvra Bhattacharyya University of Maryland, USA, and Tampere University of Technology, Finland [biography]

Shuvra S. Bhattacharyya is a Professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He holds a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS), and is a member of the Maryland Cybersecurity Center (MC2), and the University of Maryland Energy Research Center (UMERC). He is also a part time visiting professor in the Department of Pervasive Computing at the Tampere University of Technology, Finland, as part of the Finland Distinguished Professor Programme (FiDiPro). He is an author of six books, and over 250 papers in the areas of signal processing, embedded systems, electronic design automation, wireless communication, and wireless sensor networks. He received the B.S. degree from the University of Wisconsin at Madison, and the Ph.D. degree from the University of California at Berkeley. He has previously held industrial positions as a Researcher at the Hitachi America Semiconductor Research Laboratory (San Jose, California), and Compiler Developer at Kuck & Associates (Champaign, Illinois). He has held a visiting research position at the US Air Force Research Laboratory (Rome, New York). He is a Fellow of the IEEE. He has been a Nokia Distinguished Lecturer (Finland) and Fulbright Specialist (Austria and Germany). He has received the NSF Career Award (USA).
Andrew Elby University of Maryland, College Park [biography]

Andrew Elby's work focuses on student and teacher epistemologies and how they couple to other cognitive machinery and help to drive behavior in learning environments. His academic training was in Physics and Philosophy before he turned to science (partic
William Hawkins University of Maryland
Prof. Tudor Dumitras University of Maryland, College Park [biography]

Tudor Dumitraș is an Assistant Professor in the Electrical & Computer Engineering Department at the University of Maryland, College Park. His research focuses on Big Data approaches to problems in system security and dependability. In his previous role at Symantec Research Labs he built the Worldwide Intelligence Network Environment (WINE) - a platform for experimenting with Big Data techniques. He received an Honorable Mention in the NSA competition for the Best Scientific Cybersecurity Paper of 2012. He also received the 2011 A. G. Jordan Award from the ECE Department at Carnegie Mellon University, the 2009 John Vlissides Award from ACM SIGPLAN, and the Best Paper Award at ASP-DAC'03. Tudor holds a Ph.D. degree from Carnegie Mellon University.
Mr. Neruh Ramirez University of Maryland, Department of Electrical & Computer Engineering

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