2025 ASEE Annual Conference & Exposition

Bridging Theory and Practice: Active Learning and Real-World Applications in Mathematical Analysis Course

Presented at MATH - Hands-On Curriculum in Mathematics Education

Abstract:
This Evidence-Based Practice Paper outlines the redesign of the sophomore-level Mathematical Analysis course at Fairfield University, focusing on enhancing the practical application of mathematical concepts for engineering students. The course has been redesigned from a predominantly theoretical framework into a hands-on, project-based approach. Building upon the successful integration of MATLAB, the redesign emphasizes active learning techniques and interactive programming tasks to enhance student engagement. These methods provide students with practical experience in addressing real-world engineering challenges.
A cornerstone of the redesign is a practical project in which students gather and analyze real-time data from a flying drone equipped with an Inertial Measurement Unit (IMU). Through MATLAB, students process acceleration data, applying numerical integration to compute both velocity and position. This project reinforces essential concepts such as integration, data analysis, and mathematical modeling, while also highlighting the relevance of these techniques in real-world engineering scenarios.
The course structure strikes a balance between fundamental theory and practical applications. In the first half of the semester, students acquire core MATLAB skills, including loops, conditional statements, and plotting, alongside key mathematical principles. The second half delves into more advanced topics, such as numerical solutions for nonlinear equations, matrix analysis, and statistical modeling. This phase culminates in applied projects like the IMU data analysis, which integrates these advanced mathematical methods with practical, real-world problem-solving.
Flipped classroom techniques are employed to support this active learning environment. Students engage with online modules before class, freeing up lecture time for interactive programming exercises and collaborative problem-solving. Peer Learning Group (PLG) sessions also provide extra opportunities for practice and peer-assisted learning.
Preliminary feedback and assessment data suggest that this project-based approach significantly enhances students’ understanding of mathematical concepts and their ability to apply them in engineering contexts. By integrating MATLAB programming with real-world applications, the course prepares students with both the theoretical foundation and practical expertise required for advanced coursework and professional engineering challenges.

Authors

Dr. Djedjiga Belfadel Fairfield University [biography]

Dr. Djedjiga Belfadel is an Associate Professor and the Graduate Program Director for Electrical and Biomedical Engineering at Fairfield University, Connecticut. She earned her Ph.D. in Electrical and Computer Engineering from the University of Connecticut in 2015.
Dr. Belfadel is deeply committed to teaching, with a focus on innovative, hands-on learning approaches in STEM education. She has successfully integrated active learning strategies into her courses, particularly in first-year engineering programs, to enhance student engagement and retention. Her teaching emphasizes providing students with practical, real-world experiences that foster critical thinking, innovation, and problem-solving skills.
Through her teaching and research, Dr. Belfadel is dedicated to inspiring and preparing the next generation of STEM professionals, with a particular emphasis on increasing the representation of women and underrepresented groups in the field. Her contributions to both undergraduate and graduate education continue to have a significant impact on her students and the broader academic community.
Danushka Bandara Fairfield University [biography]

DANUSHKA BANDARA received the bachelor’s degree in Electrical Engineering from the University of Moratuwa, Sri Lanka, in 2009. He received his master’s and Ph.D. degrees in Computer Engineering and Electrical and Computer Engineering from Syracuse University, Syracuse, NY, USA, in 2013 and 2018, respectively. From 2019 to 2020, he worked as a Data Scientist at Corning Incorporated, Corning, NY, USA. Currently, he is an
Assistant Professor of Computer Science and Engineering
at Fairfield University, Fairfield, CT, USA. His Current research interests include Applied machine learning, Bioinformatics, Human-computer interaction, and Computational social science.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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