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Work in Progress: A Longitudinal Study of Students’ Conceptual Understanding of Signals and Systems

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2020 ASEE Virtual Annual Conference Content Access


Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Assessment of Learning in ECE Courses

Tagged Division

Electrical and Computer

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Paper Authors


Caroline Crockett University of Michigan

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Caroline Crockett is a graduate student at University of Michigan, working towards a PhD in electrical engineering and an engineering education research certificate. Her current research interests include image reconstruction and longitudinal conceptual understanding of signals and systems.

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Cynthia J. Finelli University of Michigan Orcid 16x16

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Dr. Cynthia Finelli is Professor of Electrical Engineering and Computer Science, Professor of Education, and Director and Graduate Chair for Engineering Education Research Programs at University of Michigan (U-M). Dr. Finelli is a fellow in the American Society of Engineering Education, a Deputy Editor of the Journal for Engineering Education, an Associate Editor of the IEEE Transactions on Education, and past chair of the Educational Research and Methods Division of ASEE. She founded the Center for Research on Learning and Teaching in Engineering at U-M in 2003 and served as its Director for 12 years. Prior to joining U-M, Dr. Finelli was the Richard L. Terrell Professor of Excellence in Teaching, founding director of the Center for Excellence in Teaching and Learning, and Associate Professor of Electrical Engineering at Kettering University.

Dr. Finelli's current research interests include student resistance to active learning, faculty adoption of evidence-based teaching practices, and the use of technology and innovative pedagogies on student learning and success. She also led a project to develop a taxonomy for the field of engineering education research, and she was part of a team that studied ethical decision-making in engineering students.

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Harry Courtney Powell University of Virginia

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Harry Powell is a Professor of Electrical and Computer Engineering in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia. After receiving a Bachelor's Degree in Electrical Engineering in1978 he was an active research and design engineer, focusing on automation, embedded systems, remote control, and electronic/mechanical co-design techniques, holding 16 patents in these areas. Returning to academia, he earned a PhD in Electrical and Computer Engineering in 2011 at the University of Virginia. His current research interests include machine learning, embedded systems, electrical power systems, and engineering education.

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This work in progress paper outlines our planned study of students’ conceptual understanding of signals and systems. Signals and systems (SS) is the focus of an electrical engineering (EE) science course at most universities, and topics in SS - such as filtering and Fourier transforms - are fundamental to control theory, signal processing, and machine learning tracks in EE. Despite the importance educators place on SS concepts, previous studies have shown that students understand few of the concepts at the end of a SS course. The purpose behind our planned study is to determine if undergraduate students learn individual SS concepts, and, if they do, when and how.

There are few studies that report on students’ conceptual understanding of SS topics one or more semesters after a SS course. This study aims to help fill this gap by examining student conceptual understanding over time. Our research questions are: (1) How many and which concepts do students learn during their signals and systems class? (2) How many and which SS concepts have students learned, retained, or forgotten as of their fourth year of undergraduate studies? (3) What factors influence the answers to the first two questions?

We will be studying undergraduate engineering students at the University of Michigan and University of Virginia during their second through fourth years. To measure conceptual understanding (research questions 1 and 2), we will use the signals and systems concept inventory (SSCI), an existing, validated 25-question multiple-choice test. Student participants will take the SSCI up to three times: the beginning and end of their SS course and the beginning of their fourth year.

Based on a literature review and our own experiences with SS, we have expectations for what factors may influence student conceptual understanding, e.g., what elective courses students take, whether students have seen a topic outside of a course, and what career options students are considering. Based on this and a qualitative analysis of focus groups that we will conduct with students, we will design a survey to measure factors which might impact conceptual understanding. A statistical analysis of this data, in conjunction with SSCI scores, will help answer research question 3.

Our goal for this study is to help educators understand how the undergraduate curricula (beyond just the SS course) is or is not meeting what we want undergraduate EE students to understand when they graduate and what could be changed to increase understanding. While we have chosen to study SS conceptual understanding, we anticipate our study will provide insights into the conceptual understanding over time in other engineering disciplines.

This work in progress paper will outline our planned methodology, describe the theories that will influence our study, and present preliminary results. Our goal is to receive feedback from the community on possible factors that influence long-term conceptual understanding to include on our surveys and to see if anyone else has, or wants to collect, SSCI data from fourth years to add to the data analysis.

Crockett, C., & Finelli, C. J., & Powell, H. C. (2020, June), Work in Progress: A Longitudinal Study of Students’ Conceptual Understanding of Signals and Systems Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35595

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