California Polytechnic University, California
April 10, 2025
April 10, 2025
April 12, 2025
Diversity
10.18260/1-2--55161
https://peer.asee.org/55161
Bailey Wall is earning a B.S. in Biomedical Engineering from California Polytechnic State University, San Luis Obispo. She is passionate about medical device innovation and the development of therapeutic technologies.
Ben Hoefer is a master's student at Cal Poly with experience in teaching and developing educational tools at both the undergraduate and graduate levels. His graduate research focuses on gas dynamics.
Eileen Rossman has a worked in various industries for over 14 years before starting a career teaching engineering. Here industry experience includes field support for Navy Nuclear refueling with Westinghouse, analysis and programming of pipeline flow sol
Brian Self obtained his B.S. and M.S. degrees in Engineering Mechanics from Virginia Tech, and his Ph.D. in Bioengineering from the University of Utah. He worked in the Air Force Research Laboratories before teaching at the U.S. Air Force Academy for seven years before joining Cal Poly, San Luis Obispo in 2006.
This is a work in progress, full paper submission, exploring the purpose and development of Adaptive Learning Modules (ALMs) in introductory engineering courses, specifically focusing on Dynamics. As a foundational course, Dynamics is critical for building core engineering knowledge but is often challenging for students due to their limited prior experience and misconceptions. Additionally, historically marginalized and underrepresented groups have struggled in foundational engineering courses, so the ALMs are designed to foster educational equity and emphasize non-traditional engineering applications. The ALMs aim to address these challenges by leveraging online tools to provide targeted, interactive support for difficult concepts, supplementing traditional classroom-based instruction.
There are two purposes of the ALMs: to reinforce understanding for all students, and to reduce performance gaps in introductory mechanics courses. By focusing on common problem areas, ALMs are designed to provide personalized feedback and guidance that promotes conceptual understanding. Key topics identified for modules in Dynamics include 2D Newton’s Second Law, the Coriolis effect, kinematics, and rigid body work and energy. The design of ALMs integrates video lectures, interactive questions, activities, and tailored feedback to guide students through these topics and improve learning outcomes.
Each module begins with an introductory video that connects the topic to a real-world application, highlighting its impact beyond the classroom. This step is intended to engage students by demonstrating the practical importance and use of the concept. Following the introduction, students select their preferred content delivery format: a short video for those who feel confident in their understanding or a longer, in-depth video for those who need more explanation. These video lectures allow students to move through content at a pace that is the most beneficial to them.
After viewing the content video, students are prompted with a formative Coupled Multiple Response question (CMR) to evaluate their understanding of the topic. The CMR questions consist of two parts. Students first answer the question and then select from a list of reasoning statements that most closely align with their thought process. These reasoning statements include both correct answers and common misconceptions, constructed based on student answers from previous Dynamics exams. This two-step style of questioning requires students to answer the question and identify their reasoning, which allows specific gaps in students’ understanding to be identified.
Based on the identified gaps, students are directed to the appropriate Supplemental Instruction (SI) video(s) tailored to their misconceptions. Depending on their previous responses, students can receive a simple video affirming their understanding, or a few SI videos to provide clarity and redirect their reasoning. The SI videos ensure that all students, regardless of their initial comprehension, receive targeted support.
After receiving feedback from the SI videos, students are directed to an interactive instructional tool, which uses a “predict, observe, explain” style of questioning. They are presented with a physical scenario and asked to predict the dynamic response. Following their initial prediction, students interact with the physical model to observe the outcome and explain their observations. To reinforce understanding, follow-up scenarios with slightly modified initial conditions are used to deepen and solidify understanding. The instructional tools can be used in a classroom setting with the physical models, or a virtual setting, using a simulation-based version. Each module ends with a summative question, designed for students to reflect on their learning and solidify their understanding of the topic. To reinforce key takeaways, students are also asked to complete reflection questions, which encourage them to summarize the main concepts of the topic.
The next phase of this study is to implement the Dynamics ALMs in dynamics classes at California Polytechnic State University, San Luis Obispo. Feedback from this study will be collected to determine the effectiveness of the module in improving understanding and fostering engagement. The comprehension of students before and after working through the modules will be evaluated to investigate the impact of the ALMs.
By integrating adaptive technology with traditional teaching methods, the ALMs can potentially transform the teaching of foundational engineering concepts. This approach enhances accessibility, personalizes learning experiences, and engages students more effectively, representing a significant step forward in engineering education.
Wall, B. A., & Hoefer, B. J., & Rossman, E. W., & Self, B. P. (2025, April), Adaptive Learning Modules for Introductory Engineering Courses Paper presented at 2025 ASEE PSW Conference, California Polytechnic University, California. 10.18260/1-2--55161
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