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The influence of constructing robot's behavior on the development of theory of mind (ToM) and theory of artificial mind (ToAM) in young children

Published:21 June 2015Publication History

ABSTRACT

A new theoretical scheme named ToAM (Theory of Artificial Mind) was examined by means of qualitative and quantitative methodology among twenty four 5-7 year old children from centr al Israel. The study also examined the effects of interacting with behaving artifacts (constructing versus observing the robot's behavior) using the "RoboGan" interface on children's development of ToAM and ToM and looked for conceptions that evolve among children while interacting with behaving artifacts which are indicative of the acquisition of ToAM. The quantitative analysis indicated that the interaction with behaving artifacts, for both age and condition groups brought into awareness children's ToM as well as influenced their ability to understand that robots can behave independently and based on external and environmental conditions. The qualitative analysis indicated that the engagement in building the robot's behavior influenced the constructors' ability to explain several of the robots' behaviors, their understanding of the robot's script-based behavior and rule-based behavior and the children's metacognitive development. The theoretical and practical importance of the study is discussed.

References

  1. Altarriba, J., Bauer, L. M., & Benvenuto, C. (1999). Concreteness, context availability, and imageability ratings and word associations for abstract, concrete and emotion words. Behavior Research Methods, Instruments, & Computers, 31, 578--602.Google ScholarGoogle ScholarCross RefCross Ref
  2. Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computaional thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145--157. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Burke Johnson, R., & Onwuegbuzie, A. J. (2004). Mixed Methods Research: A research paradigm whose time has come. Educational Researcher, 33(7), 14--26.Google ScholarGoogle ScholarCross RefCross Ref
  4. Caci, B., D'amico, A. & Chiazzese, G. (2012). Robotics and virtual worlds: an experiential learning llab. Advances in Intelligent Systems and Computing, 196, 83--87.Google ScholarGoogle ScholarCross RefCross Ref
  5. Duncker, K. (1945). On problem solving. Psychological Monographs, 58, 5 (Whole No. 270).Google ScholarGoogle ScholarCross RefCross Ref
  6. German, T. P. & Defeyter, M. A. (2000). Immunity to functional fixedness in young chidren. Psychonomic Bulletin & Review, 7(4), 707--7112.Google ScholarGoogle ScholarCross RefCross Ref
  7. Granott, N. (1991). Puzzled minds and weird creatures: Phases in the spontaneous process of knowledge construction. In I. Harel & S. Papert (Eds.) Constructionism. Norwood, NJ: Ablex.Google ScholarGoogle Scholar
  8. Kaufman, A. S. & Kaufman, N. L. (1983). Kaufman Assessment Battery for Children (K-ABC). Pearson Assessments, Bloomington, MN.Google ScholarGoogle Scholar
  9. Kazakoff, E. R., Sullivan, A., & Bers, A. U. (2013). The effect of a classroom-based intensive robotics and programming workshop on sequencing ability in early childhood. Early Childhood Education Journal, 41, 245--255.Google ScholarGoogle ScholarCross RefCross Ref
  10. Kramarski, B., Mevarech, Z., & Arami, M. (2002). The effects of metacognitive instruction on solving mathematical authentic tasks. Educational Studies in Mathematics, 49(2), 225--250.Google ScholarGoogle ScholarCross RefCross Ref
  11. Levy, S. T., & Mioduser, D. (2008). Does it "want" or "was it programmed to..."? Kindergarten children's explanations of an autonomous robots' adaptive functioning. International Journal of Technology and Design Education, 18, 337--359.Google ScholarGoogle Scholar
  12. Matan, A., & Carey, S. (2001). Developmental changes within the core of artifact concepts. Cognition, 78, 1--26.Google ScholarGoogle ScholarCross RefCross Ref
  13. Mioduser, D., & Kuperman, A. (2012). Kindergarten children's perceptions of "Anthropomorphic Artifacts" with adaptive behavior. Proceedings of the Chais conference on instructional technologies research 2012: Learning in the Technological era. Y. Eshet-Alkalai, A. Caspi, S. Eden., N. Geri., Y. Yair, Y. Kalma. (Eds.), Raanana: The Open University of Israel.Google ScholarGoogle Scholar
  14. Mioduser, D., & Levy, S. T. (2010). Making sense by building sense: Kindergarten children's construction and understanding of adaptive robot behavior. International Journal of Computers in Mathematical learning, 15, 99--127.Google ScholarGoogle ScholarCross RefCross Ref
  15. Mioduser, D., Levy, S. T., & Talis, V. (2009). Episodes to Scripts to Rules: Concrete-abstractions in kindergarten children's explanations of a robot's behavior. International Journal of Technology and Design Education, 19, 15--36.Google ScholarGoogle ScholarCross RefCross Ref
  16. Papert, S. (1980). Mindstorms: children, computers and powerful Ideas. NY: Harvester Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Perner J., & Wimmer, H. (1985). John thinks that Mary thinks that: attribution of second order beliefs by 5-year-old to 10-year-old children. Journal of Experimental Child Psychology, 39, 437--71.Google ScholarGoogle ScholarCross RefCross Ref
  18. Peyser, M., Shimborsky, G., Wolf, N., & Hazany, I. (1996). Kaufman assessment battery for children: Israeli version. Jerusalem: Ministry of education, culture and sports - psychological and counseling services, the Henrietta Szold institute for research in behavioral sciences.Google ScholarGoogle Scholar
  19. Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a 'theory of mind'? Behavioral and Brain Sciences, 4, 515--526.Google ScholarGoogle ScholarCross RefCross Ref
  20. Resnick, M. (1998). Technologies for Lifelong Kindergarten. Educational Technology Research & Development, 46(4), 43--55.Google ScholarGoogle ScholarCross RefCross Ref
  21. Sammeroff, A, & Haith, M. (1996). The five to seven year shift. Chicago, IL: The University of Chicago Press.Google ScholarGoogle Scholar
  22. Siegler, R. S. & Chen, Z. (1998). Developmental differences in rule learning: A microgenetic analysis. Cognitive Psychology, 36, 273--310.Google ScholarGoogle ScholarCross RefCross Ref
  23. Talis, V., Levy, S. T. & Mioduser, D. (1998). RoboGAN: Interface for programming a robot with rules for young children. Tel-Aviv University.Google ScholarGoogle Scholar
  24. Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children's understanding of deception. Cognition, 13, 103--128.Google ScholarGoogle ScholarCross RefCross Ref

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  1. The influence of constructing robot's behavior on the development of theory of mind (ToM) and theory of artificial mind (ToAM) in young children

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    • Published in

      cover image ACM Conferences
      IDC '15: Proceedings of the 14th International Conference on Interaction Design and Children
      June 2015
      488 pages
      ISBN:9781450335904
      DOI:10.1145/2771839

      Copyright © 2015 ACM

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      Publication History

      • Published: 21 June 2015

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