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.

@inproceedings{wu2023undergraduate,
  title={Undergraduate Robotics Education with General Instructors Using a Student-Centered Personalized Learning Framework},
  author={Rui Wu and David Feil-Seifer and Ponkoj C. Shill and Hossein Jamali and Sergiu Dascalu and Fredrick C. Harris},
  year={2023},
  month={June},
  url={https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Wfm3Z_YAAAAJ&citation_for_view=Wfm3Z_YAAAAJ:eQOLeE2rZwMC},
  publisher={ASEE},
  booktitle={2024 ASEE Annual Conference & Exposition, 2024},
}

Collaborative Research: A Student-Centered Personalized Learning Framework to Advance Undergraduate Robotics Education, National Science Foundation PI: David Feil-Seifer, co-PI: Fredrick Harris, Sergiu Dascalu, Amount: $320,214, June 1, 2022 - May 31, 2025