Adaptive Learning Platform for Engineering Dynamics

Track: Student Success & Wellness Engineering Dynamics is a foundational junior‑level mechanical engineering course that focuses on the mathematical modeling and dynamic analysis of a broad spectrum of systems—from translational and rotational mechanics to thermal processes, multi‑degree‑of‑freedom mechanisms, and electromechanical and electrical subsystems—using differential equations, Laplace transforms, and transfer functions. To address both the rigor of this mathematical content and the diversity of student preparedness, we developed an adaptive learning framework with the Realizeit platform and seamlessly integrated it into UNC Charlotte’s Canvas environment. Key concepts in Dynamics 2 were mapped into a hierarchical prerequisite network of modules and nodes, each containing instructional materials, randomized practice problems, and auto‑graded assessments, including MATLAB Grader for coding tasks. Standalone exam modules provided secure, timed evaluations of mastery. Realizeit’s analytics dashboard enabled real‑time monitoring of student progress and classification of learners as high achievers, struggling students, or inconsistent performers. Based on these insights, we deployed targeted interventions—including personalized messages, supplemental videos, and concise lecture notes—which students reported made them feel more confident and supported. Preliminary outcomes indicate increased engagement, higher assignment completion rates, deeper conceptual mastery, and an overall positive learning experience. Challenges included reduced in‑class attendance and the resource demands of content development. Future directions involve refining intervention strategies, incentivizing attendance with challenge problems, and extending the adaptive framework to other STEM courses. This work demonstrates a scalable approach for integrating adaptive learning technologies to personalize instruction and enhance student success in mathematically intensive engineering curricula.

Publication Details

Journal
Dialogues in Social Justice: An Adult Education Journal (The University of North Carolina at Charlotte)
Published
2025-10-16
Primary Topic
Innovative Teaching Methods
Type
article
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article

Adaptive Learning Platform for Engineering Dynamics

Dialogues in Social Justice: An Adult Education Journal (The University of North Carolina at Charlotte)
Innovative Teaching Methods
article

Adaptive Learning Platform for Engineering Dynamics

article en

Abstract

Track: Student Success & Wellness Engineering Dynamics is a foundational junior‑level mechanical engineering course that focuses on the mathematical modeling and dynamic analysis of a broad spectrum of systems—from translational and rotational mechanics to thermal processes, multi‑degree‑of‑freedom mechanisms, and electromechanical and electrical subsystems—using differential equations, Laplace transforms, and transfer functions. To address both the rigor of this mathematical content and the diversity of student preparedness, we developed an adaptive learning framework with the Realizeit platform and seamlessly integrated it into UNC Charlotte’s Canvas environment. Key concepts in Dynamics 2 were mapped into a hierarchical prerequisite network of modules and nodes, each containing instructional materials, randomized practice problems, and auto‑graded assessments, including MATLAB Grader for coding tasks. Standalone exam modules provided secure, timed evaluations of mastery. Realizeit’s analytics dashboard enabled real‑time monitoring of student progress and classification of learners as high achievers, struggling students, or inconsistent performers. Based on these insights, we deployed targeted interventions—including personalized messages, supplemental videos, and concise lecture notes—which students reported made them feel more confident and supported. Preliminary outcomes indicate increased engagement, higher assignment completion rates, deeper conceptual mastery, and an overall positive learning experience. Challenges included reduced in‑class attendance and the resource demands of content development. Future directions involve refining intervention strategies, incentivizing attendance with challenge problems, and extending the adaptive framework to other STEM courses. This work demonstrates a scalable approach for integrating adaptive learning technologies to personalize instruction and enhance student success in mathematically intensive engineering curricula.

Dialogues in Social Justice: An Adult Education Journal (The University of North Carolina at Charlotte)
Quality Education
Openalex Percentile: Top 24%
Innovative Teaching Methods
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