  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.
