BOARD # 443: RIEF: Implementing problem-based learning to facilitate problem abstraction skills in a statics course

Nigel Berkeley Kaye; Lisa Benson; Evan Taylor; Makayla Headley

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Conference: 2025 ASEE Annual Conference & Exposition
Location: Montreal, Quebec, Canada
Publication Date: June 22, 2025
Start Date: June 22, 2025
End Date: August 15, 2025
Conference Session: NSF Grantees Poster Session II
Tagged Topics: Diversity and NSF Grantees Poster Session
Page Count: 6
DOI: 10.18260/1-2--55823
Permanent URL: https://peer.asee.org/55823
Download Count: 1

Paper Authors

biography

Nigel Berkeley Kaye Clemson University orcid.org/0000-0001-7190-7791

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Nigel Kaye is a Professor in the Glenn Department of Civil Engineering at Clemson University. His primary research interests are in the fluid mechanics of natural hazards and in exploring ways to teach mechanics that improve student self-efficacy.

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biography

Lisa Benson Clemson University orcid.org/0000-0001-5517-2289

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Lisa Benson is a Professor of Engineering and Science Education at Clemson University, and the past editor of the Journal of Engineering Education. Her research focuses on the interactions between student motivation and their learning experiences. Her projects include studies of student perceptions, beliefs and attitudes towards becoming engineers and scientists, and their development of problem-solving skills, self-regulated learning practices, and epistemic beliefs. Other projects in the Benson group involve students’ navigational capital, and researchers’ schema development through the peer review process. Dr. Benson is an American Society for Engineering Education (ASEE) Fellow, and a member of the European Society for Engineering Education (SEFI), American Educational Research Association (AERA) and Tau Beta Pi. She earned a B.S. in Bioengineering (1978) from the University of Vermont, and M.S. (1986) and Ph.D. (2002) in Bioengineering from Clemson University.

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Evan Taylor Clemson University orcid.org/0000-0003-1974-8978

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Evan Taylor is a Ph.D. candidate in the Department of Mechanical Engineering at Clemson University. His research through the VIPR-GS focuses on model-based systems engineering of ground vehicles. As a senior member of the CEDAR design group, he actively mentors and collaborates with fellow researchers. He plans to propose his dissertation on model fidelity evaluation and model selection in May 2025. He also develops his skills as an educator and community leader through education research and service in Graduate Student Government.

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Makayla Headley Clemson University orcid.org/0009-0003-2941-7854

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Makayla Headley is a doctoral student in the Department of Engineering and Science Education at Clemson University and an NSF Bridge to Doctorate Fellow. In addition to her Ph.D. studies, she is pursuing a Master of Science in Computer Science with a concentration in Software Engineering. She earned a B.S. in Chemical Engineering from the University of Maryland, Baltimore County (UMBC). Her dissertation research centers on engaging engineering students in the accreditation process, with the goal of aligning accreditation practices with students’ career readiness. Through this work, she aims to Elevate STEM Students’ Outlooks (ESSO).

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Abstract

This poster will report on the progress made in the second (implementation) phase of a project funded through the NSF Research Initiation in Engineering Formation (RIEF) program. The project is focused on students’ problem-solving skill acquisition in a sophomore level engineering mechanics course (statics) with emphasis on building their skills related to problem abstraction. The first phase of the project involved planning and development of course materials and research studies. The second phase of the study involves teaching the course using instructional approaches that allow for students to practice developing problem abstraction skills through physical models and group problem solving. This poster will provide a summary of lessons learned in the implementation phase of the project, specifically the use of physical models, shared group explanations of problem framing and solutions, homework problems, test questions, reflection prompts and problem-solving assessment techniques.

Instructional approaches in this course were designed to encourage cooperative learning. Students were organized into teams by the instructor primarily based on compatibility of students’ schedules. Teams began working together by collaboratively developing team contracts outlining roles and expectations. Teams worked together in class on problems and outside of class on homework problems. In-class problems often included analysis and manipulation of physical models to aid in the development of problem abstraction skills. Groups were also responsible for reporting out to the class on their homework solutions.

Students’ problem solving skills were assessed using an established rubric that gives students feedback on how well they completed various steps in the problem solving process, including developing a problem statement, representing the problem with a free body diagram, organization of the information provided, use of equations and calculations, explanations of solution and checking for accuracy. Students were also prompted to rate their confidence in their knowledge needed to complete the problem, the amount of effort they put into the problem, their level of frustration, and their confidence in being able to solve a similar problem in the future.

Indicators of student learning and the success of instructional approaches used in the course include observations about student engagement in the course activities, student performance on homework problems and tests, students’ self-reported confidence in their knowledge and skills, and how well teams are functioning in the team-based approach to problem solving using an established teamwork survey (ITP Metrics).

Preliminary results show student engagement is as anticipated: students are explaining their homework problem solutions to peers, working on teams on homework problem sets, manipulating the physical models (with guidance) in class. All students completed team contracts and engaged with their teams effectively to submit assignments. Initial results from graded homework problems indicate that students are feeling confident in their knowledge to complete the problems and in their ability to solve similar problems in the future. Challenges to implementing these instructional approaches include timing of class activities, specifically the amount of time that students took to work with the physical models, and the time involved with developing class activities.

Citation
Format

Kaye, N. B., & Benson, L., & Taylor, E., & Headley, M. (2025, June), BOARD # 443: RIEF: Implementing problem-based learning to facilitate problem abstraction skills in a statics course Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--55823

TY  - CPAPER
AB  - This poster will report on the progress made in the second (implementation) phase of a project funded through the NSF Research Initiation in Engineering Formation (RIEF) program. The project is focused on students’ problem-solving skill acquisition in a sophomore level engineering mechanics course (statics) with emphasis on building their skills related to problem abstraction. The first phase of the project involved planning and development of course materials and research studies. The second phase of the study involves teaching the course using instructional approaches that allow for students to practice developing problem abstraction skills through physical models and group problem solving. This poster will provide a summary of lessons learned in the implementation phase of the project, specifically the use of physical models, shared group explanations of problem framing and solutions, homework problems, test questions, reflection prompts and problem-solving assessment techniques. 

Instructional approaches in this course were designed to encourage cooperative learning. Students were organized into teams by the instructor primarily based on compatibility of students’ schedules. Teams began working together by collaboratively developing team contracts outlining roles and expectations. Teams worked together in class on problems and outside of class on homework problems. In-class problems often included analysis and manipulation of physical models to aid in the development of problem abstraction skills. Groups were also responsible for reporting out to the class on their homework solutions.  

Students’ problem solving skills were assessed using an established rubric that gives students feedback on how well they completed various steps in the problem solving process, including developing a problem statement, representing the problem with a free body diagram, organization of the information provided, use of equations and calculations, explanations of solution and checking for accuracy. Students were also prompted to rate their confidence in their knowledge needed to complete the problem, the amount of effort they put into the problem, their level of frustration, and their confidence in being able to solve a similar problem in the future. 

Indicators of student learning and the success of instructional approaches used in the course include observations about student engagement in the course activities, student performance on homework problems and tests, students’ self-reported confidence in their knowledge and skills, and how well teams are functioning in the team-based approach to problem solving using an established teamwork survey (ITP Metrics).

Preliminary results show student engagement is as anticipated: students are explaining their homework problem solutions to peers, working on teams on homework problem sets, manipulating the physical models (with guidance) in class. All students completed team contracts and engaged with their teams effectively to submit assignments. Initial results from graded homework problems indicate that students are feeling confident in their knowledge to complete the problems and in their ability to solve similar problems in the future. Challenges to implementing these instructional approaches include timing of class activities, specifically the amount of time that students took to work with the physical models, and the time involved with developing class activities.
AU  - Nigel Berkeley Kaye
AU  - Lisa Benson
AU  - Evan Taylor
AU  - Makayla Headley
CY  - Montreal, Quebec, Canada 
DA  - 2025/06/22
PB  - ASEE Conferences
TI  - BOARD # 443: RIEF: Implementing problem-based learning to facilitate problem abstraction skills in a statics course
UR  - https://peer.asee.org/55823
DO  - 10.18260/1-2--55823
ER  -