Robotics in the Classroom

thumbnail for Robotics in the Classroom Robotics represents one of the key areas for economic development and job growth in the US. However, the current training paradigm for robotics instruction relies on primarily graduate study. Some advanced undergraduate courses may be available, but students typically have access to at most one or two of these courses. The result of this configuration is that students need several years beyond an undergraduate degree to gain mastery of robotics in the academic setting. This project aims to: alter current robotics courses to make them accessible for lower-division students; increase both the depth and breadth of the K-12 robotics experience; increase the portability of robotics courses by disseminating course materials online, relying on free and open-source software (FOSS), and promoting the use of simulators and inexpensive hardware. We will team with educators to study the effectiveness of the generated materials at promoting interest in robotics, computing, and technology at the K-5, 6-8, 9-12, and undergraduate grade levels.



  • Miller, B., Anderson, M., Major, J., Jurkiewicz, M., Kirn, A., & Feil-Seifer, D. Unplugged Robotics to Increase K-12 Students' Engineering Interest and Attitudes. In Frontiers in Education, San Jose, CA, Oct 2018. ( details ) ( .pdf )
  • Anderson, M., Miller, B., Kirn, A., Jurkiewicz, M., & Feil-Seifer, D. Making in the Middle: Robots and Sequences. In ScienceScope, Feb 2019. ( details )
  • Rand, K., Sengupta, S., & Feil-Seifer, D. Unplugged Robotics as a Platform for Cybersecurity Education in the Elementary Classroom. In Colloquium for Information Systems Security Education, New Orleans, LA, Jun 2018. ( details ) ( .pdf )
  • Blankenburg, J., Kelley, R., Feil-Seifer, D., Wu, R., Barford, L., & Harris, C. F. Towards GPU-Accelerated PRM for Autonomous Navigation. In International Conference on Information Technology : New Generations (ITNG), Las Vegas, NV, Apr 2020. ( details )
  • Blankenburg, J., Zagainova, M., Simmons, M. S., Talavera, G., Nicolescu, M., & Feil-Seifer, D. Human-Robot Collaboration and Dialogue for Fault Recovery on Hierarchical Tasks. In International Conference on Social Robotics (ICSR), CO, Oct 2020. ( details ) ( .pdf )
  • Bas, E. E., Moustafa, M., Feil-Seifer, D., & Blankenburg, J. Using a Machine Learning Approach for Computational Substructure in Real-Time Hybrid Simulation. In IMAC-XXXVIII Conference and Exposition, Houston, TX, SEM. Feb 2020. SEM. ( details )
  • Barchard, K., Lapping-Carr, L., Westfall, S., Fink-Armold, A., Banisetty, S., & Feil-Seifer, D. Measuring the Perceived Social Intelligence of Robots. In ACM Transactions on Human-Robot Interaction (THRI), 9(4):1-29, Sep 2020. ( details ) ( .pdf )
  • Barchard, K., Lapping-Carr, L., Westfall, S., Banisetty, S., & Feil-Seifer, D. Measuring 20 aspects of the perceived social intelligence of robots. Poster Paper in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, Oct 2018. ( details )
  • Barchard, K., Lapping-Carr, L., Westfall, S., & Feil-Seifer, D. Perceived social intelligence of robots.. To Appear in Society for Personality and Social Psychology, Portland, Oregon, Feb 2019. ( details )
  • Barchard, K., Lapping-Carr, L., Westfall, S., Banisetty, S., & Feil-Seifer, D. Perceived Social Intelligence (PSI) Scales test manual. Unpublished psychological test and test manual. Observer report of 20 aspects of social intelligence of robots, with four items per scale. Technical Report, Aug 2018. ( details ) ( .pdf )