Logistics of Mathematical Modeling-Focused Projects
R. Corban Harwood

TL;DR
This paper offers practical guidance for implementing mathematical modeling projects in undergraduate courses, emphasizing logistics, assessment, and student engagement to improve learning outcomes.
Contribution
It provides a comprehensive overview of logistics, assessment tools, and best practices for successfully integrating modeling projects in undergraduate mathematics classes.
Findings
Student feedback improved with guided project transitions
Projects enhanced understanding of course topics
Logistical insights aid successful implementation
Abstract
This article addresses the logistics of implementing projects in an undergraduate mathematics class and is intended both for new instructors and for instructors who have had negative experiences implementing projects in the past. Project implementation is given for both lower and upper division mathematics courses with an emphasis on mathematical modeling and data collection. Projects provide tangible connections to course content which can motivate students to learn at a deeper level. Logistical pitfalls and insights are highlighted as well as descriptions of several key implementation resources. Effective assessment tools, which allowed me to smoothly adjust to student feedback, are demonstrated for a sample class. As I smoothed the transition into each project and guided students through the use of the technology, their negative feedback on projects decreased and more students noted…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStatistics Education and Methodologies · Engineering Education and Pedagogy
