Undergraduate Robotics Education with General Instructors using a Student-Centered Personalized Learning Framework

TL;DR

This paper introduces a student-centered personalized learning framework for undergraduate robotics education, enabling general instructors to tailor courses to diverse student backgrounds and preferences through modular, graph-structured content.

Contribution

The proposed framework allows general instructors to deliver flexible, customizable robotics courses by breaking down topics into dependencies and supporting personalized learning paths.

Findings

User study shows improved student engagement and learning outcomes.

Framework effectively accommodates diverse student backgrounds.

Modular approach simplifies course customization for different institutions.

Abstract

Recent advancements in robotics, including applications like self-driving cars, unmanned systems, and medical robots, have had a significant impact on the job market. On one hand, big robotics companies offer training programs based on the job requirements. However, these training programs may not be as beneficial as general robotics programs offered by universities or community colleges. On the other hand, community colleges and universities face challenges with required resources, especially qualified instructors, to offer students advanced robotics education. Furthermore, the diverse backgrounds of undergraduate students present additional challenges. Some students bring extensive industry experiences, while others are newcomers to the field. To address these challenges, we propose a student-centered personalized learning framework for robotics. This framework allows a general instructor to teach undergraduate-level robotics courses by breaking down course topics into smaller components with well-defined topic dependencies, structured as a graph. This modular approach enables students to choose their learning path, catering to their unique preferences and pace. Moreover, our framework's flexibility allows for easy customization of teaching materials to meet the specific needs of host institutions. In addition to teaching materials, a frequently-asked-questions document would be prepared for a general instructor. If students' robotics questions cannot be answered by the instructor, the answers to these questions may be included in this document. For questions not covered in this document, we can gather and address them through collaboration with the robotics community and course content creators. Our user study results demonstrate the promise of this method in delivering undergraduate-level robotics education tailored to individual learning outcomes and preferences.