skip to main content
10.1145/2559636.2559671acmconferencesArticle/Chapter ViewAbstractPublication PageshriConference Proceedingsconference-collections
research-article

Personalizing robot tutors to individuals' learning differences

Published:03 March 2014Publication History

ABSTRACT

In education research, there is a widely-cited result called "Bloom's two sigma" that characterizes the differences in learning outcomes between students who receive one-on-one tutoring and those who receive traditional classroom instruction. Tutored students scored in the 95th percentile, or two sigmas above the mean, on average, compared to students who received traditional classroom instruction. In human-robot interaction research, however, there is relatively little work exploring the potential benefits of personalizing a robot's actions to an individual's strengths and weaknesses. In this study, participants solved grid-based logic puzzles with the help of a personalized or non-personalized robot tutor. Participants' puzzle solving times were compared between two non-personalized control conditions and two personalized conditions (n=80). Although the robot's personalizations were less sophisticated than what a human tutor can do, we still witnessed a "one-sigma" improvement (68th percentile) in post-tests between treatment and control groups. We present these results as evidence that even relatively simple personalizations can yield significant benefits in educational or assistive human-robot interactions.

References

  1. B. S. Bloom, "The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring." Educational Researcher, vol. 13, no. 6, pp. 4--16, 1984.Google ScholarGoogle ScholarCross RefCross Ref
  2. M. K. Lee, J. Forlizzi, S. B. Kiesler, P. E. Rybski, J. Antanitis, and S. Savetsila, "Personalization in HRI: a longitudinal field experiment." 7th ACM/IEEE International Conference on Human-Robot Interaction, pp. 319--326, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. K. VanLehn, "The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems," Educational Psychologist, vol. 46, no. 4, pp. 197--221, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  4. R. Nkambou, J. Bourdeau, and V. Psyché, "Building Intelligent Tutoring Systems: An overview," Advances in Intelligent Tutoring Systems, pp. 361--375, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  5. C. D. Kidd and C. Breazeal, "Robots at home: Understanding long-term human-robot interaction," 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3230--3235, 2008.Google ScholarGoogle Scholar
  6. J.-Y. Sung, R. E. Grinter, and H. I. Christensen, "Pimp My Roomba": designing for personalization." Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 193--196, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. R. Movellan, F. Tanaka, I. R. Fasel, C. Taylor, P. Ruvolo, and M. Eckhardt, "The RUBI project: A progress report," 2nd ACM/IEEE International Conference on Human-Robot Interaction, pp. 333--339, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. E. Hyun, H. Yoon, and S. Son, "Relationships between user experiences and children's perceptions of the education robot," 5th ACM/IEEE International Conference on Human-Robot Interaction, pp. 199--200, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Bennewitz, F. Faber, D. Joho, M. Schreiber, and S. Behnke, "Towards a humanoid museum guide robot that interacts with multiple persons," 5th IEEE-RAS International Conference on Humanoid Robots, pp. 418--423, dec. 2005.Google ScholarGoogle Scholar
  10. J. K. Lee, R. Toscano, W. Stiehl, and C. Breazeal, "The design of a semi-autonomous robot avatar for family communication and education," Robot and Human Interactive Communication, 2008. RO-MAN 2008. The 17th IEEE International Symposium on, pp. 166 --173, aug. 2008.Google ScholarGoogle Scholar
  11. I. Leite, G. Castellano, A. Pereira, C. Martinho, and A. Paiva, "Long-term interactions with empathic robots: Evaluating perceived support in children," Lecture Notes in Computer Science, vol. 7621, pp. 298--307, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. D. Leyzberg, S. Spaulding, M. Toneva, and B. Scassellati, "The physical presence of a robot tutor increases cognitive learning gains," in Proceedings of the 34th Annual Conference of the Cognitive Science Society. Austin,TX: Cognitive Science Society, 2012.Google ScholarGoogle Scholar
  13. H. Kozima, C. Nakagawa, and Y. Yasuda, "Interactive robots for communication-care: A case-study in autism therapy," IEEE International Symposium on Robot and Human Interactive Communication, 2005.Google ScholarGoogle Scholar
  14. D. Leyzberg, E. Avrunin, J. Liu, and B. Scassellati, "Robots that express emotion elicit better human teaching," in 6th International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2011, pp. 347--354. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. C.-H. Yu, H.-L. Lee, and L.-H. Chen, "An efficient algorithm for solving nonograms," Applied Intelligence, vol. 35, no. 1, pp. 18--31, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Personalizing robot tutors to individuals' learning differences

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Conferences
            HRI '14: Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
            March 2014
            538 pages
            ISBN:9781450326582
            DOI:10.1145/2559636

            Copyright © 2014 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 3 March 2014

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article

            Acceptance Rates

            HRI '14 Paper Acceptance Rate32of132submissions,24%Overall Acceptance Rate242of1,000submissions,24%

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader