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2026 ASEE Annual Conference & Exposition

IUSE: Motivation and Cognitive Engagement in Engineering Courses: Employing a Learning Management System to Present Pre-Requisite Content for Classroom Preparation

Presented at NSF Grantees Poster Session II

Academic motivation and in-class cognitive engagement are affective measures that positively impact learning and performance in higher education. This research article quantifies the academic motivation and in-class cognitive engagement of students in four separate engineering courses at three different universities when prerequisite content is assigned before class using a Learning Management System (LMS). The content was assigned weekly to students in mechanical, electrical, civil, and industrial engineering programs prior to lecture, facilitating the implementation of active learning within a blended classroom model.

Academic motivation and cognitive engagement were measured using two established instruments from existing literature: the MUSIC Model of Academic Motivation and the Student Course Cognitive Engagement Inventory (SCCEI). The MUSIC model encompasses five dimensions of the academic motivation construct: Empowerment, Usefulness, Success, Interest, and Caring. The SCCEI also has five dimensions that align with the ICAP (Interactive, Constructive, Active, and Passive) framework for active learning: Peer Interactivity, Constructive Notetaking, Active Notetaking, Active Processing, and Passive Processing.

For each course, descriptive statistics for the various dimensions of the MUSIC and SCCEI instruments will be presented and discussed, and comparisons will be made among the courses. Correlations between the MUSIC and SCCEI dimensions will also be explored. The results from the four courses will allow comparison across contexts, including different academic levels, universities, engineering majors, and subjects. This study is part of a larger study to compare two online platforms for presenting and assessing pre-class, pre-requisite content in engineering courses. The two platforms are the CANVAS learning management system (LMS) and the RealizeIT adaptive learning platform (ALP), which is designed for personalized education. Our goal is to identify the preferred platform based on these affective measures as well as direct measures of student learning.

Authors

Dr. Renee M Clark University of Pittsburgh [biography]

Dr. Renee Clark is Associate Professor of Industrial Engineering at the University of Pittsburgh. She also serves as a Data Engineer and Director of Assessment for the Engineering Education Research Center (EERC) within the Swanson School of Engineering at Pitt. She uses data analytics to study techniques and approaches in engineering education, with a focus on active learning techniques and the professional formation of engineers. Dr. Clark is currently funded as Principal Investigator by the National Science Foundation for her research, which includes defining and assessing engineering judgment as well as the use of adaptive online learning in the engineering classroom, for which she is developing the BeSharpStats Youtube channel. Dr. Clark teaches Statistics for IE undergraduates and also serves as a study abroad instructor. She is an Associate Editor for Advances in Engineering Education. She has over 30 years of experience as an engineer and IT analyst in industry and academia. She completed her post-doctoral studies in engineering education at the University of Pittsburgh.
Prof. Autar Kaw http://orcid.org/0000-0002-3976-6375 University of South Florida [biography]

Autar Kaw is a Professor of Mechanical Engineering and the Jerome Krivanek Distinguished Teacher at the University of South Florida, nationally recognized for his contributions to engineering education. He earned his Ph.D. in Engineering Mechanics from Clemson University. Professor Kaw’s work spans engineering education research, personalized and blended learning, flipped classrooms, open courseware development, composite materials mechanics, sports analytics, and bascule bridge design. His research has been supported by the National Science Foundation, Air Force Office of Scientific Research, Florida Department of Transportation, and Wright-Patterson Air Force Base. Since 2001, he has served as the lead Principal Investigator on seven NSF-funded engineering education projects totaling $3.3 million. These initiatives have explored the impact of innovative learning environments on metacognitive development, conceptual understanding through multiple representations, group collaboration, student perceptions, and activation of prior knowledge. Under his leadership, his team developed and refined open educational resources (OERs) in Numerical Methods, which attract over 1 million page views and YouTube lecture views annually, and 60,000 visitors to the widely followed “Numerical Methods Guy” blog. Professor Kaw has authored more than 135 refereed technical papers, and his opinion pieces have appeared in The Tampa Bay Times, The Tampa Tribune, and The Chronicle of Higher Education. His work has been featured and cited in Inside Higher Ed, ASEE Prism, Voice of America, NSF Discovery, The Chronicle of Higher Education, the U.S. Congressional Record, and Florida Senate Resolution. Among his many honors, he received the 2012 U.S. Professor of the Year Award for doctoral and research universities, presented by the Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education.
Dr. Ahmed Dallal http://orcid.org/0000-0003-0573-2326 University of Pittsburgh [biography]

Dr. Dallal is an associate professor at the Department of Electrical and Computer Engineering, University of Pittsburgh. Dr. Dallal's primary focus is on education development and innovation. His research interests include biomedical signal processing, biomedical image analysis, and computer vision, as well as machine learning, networked control systems, and human-machine learning.
Kelly Maren Kibler University of Central Florida [biography]

Dr. Kelly Kibler is an Associate Professor of Water Resources Engineering in the Department of Civil, Environmental and Construction Engineering at the University of Central Florida. She is faculty of UCF’s National Center for Integrated Coastal Research and a Faculty Fellow of UCF’s Center for Global Economic and Environmental Opportunity. Dr. Kibler obtained her Ph.D. in Water Resources Engineering and M.Sc. in Forest Engineering from Oregon State University, and her B.Sc. In Environmental Science from the University of North Carolina at Chapel Hill. Dr. Kibler worked with the United Nations Environmental, Scientific and Cultural Organization (UNESCO) before joining UCF faculty, where she teaches Engineering Fluid Mechanics, Open Channel Hydraulics, Ecohydraulics and Water Policy.
Dr. Kibler’s Ecohydraulics Laboratory conducts interdisciplinary research at the crossroads of water resources engineering and aquatic ecology. Targeting coupled biological and physical variables in river and estuarine systems, the Kibler Ecohydraulics Lab advances basic scientific knowledge in flow-biota interaction and its influence to hydrodynamics and sediment transport. Dr. Kibler’s research findings are applied to the design of natural infrastructure used to protect communities from climatic hazards, such as erosion and flooding. The Ecohydraulics Lab’s study of environmental fluid mechanics within complex three-dimensional canopies improves understanding of flow resistance and sediment transport mechanisms within natural aquatic features, such as vegetation or shellfish reefs. Dr. Kibler’s research has been supported by grants from the U.S. National Science Foundation (NSF), U.S. National Oceanic and Atmospheric Administration (NOAA), the Defense Advanced Research Projects Agency (DARPA), The Nature Conservancy (TNC), Environmental Protection Agency (EPA) National Estuaries Program, Florida Department of Environmental Protection (FDEP) and Florida Department of Transportation (FDOT). Dr. Kibler is Chair of the River Restoration Technical Committee of the American Society for Civil Engineers, Associate Editor of the Journal of Hydrology, and active in committees of the American Geophysical Union.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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