Many technological artifacts (e.g., humanoid robots, computer agents) consist of biologically inspired features of human-like appearance and behaviors that elicit a social response. The strong social components of technology permit people to share information and ideas with these artifacts. As robots cross the boundaries between humans and machines, the features of human interactions can be replicated to reveal new insights into the role of social relationships in learning and creativity. Peer robots can be designed to create ideal circumstances that enable new ways for students to reflect, reason, and learn. This, in turn, has increased expectations that robots and computer agents will enhance human learning and complement people's physical, social, and cognitive capabilities. This paper explores how peer-like robots and robotic systems may help students learn and engage in creative ways of thinking.
Get full access to this article
View all access options for this article.
References
1.
BaerJ. M. (1988). Long-term effects of creativity training with middle school students. The Journal of Early Adolescence, 8(2), 183–193.
2.
BarghJ., & SchulY. (1980). On the cognitive benefits of teaching. Journal of Educational Psychology, 72, 593–604.
3.
BarronF. X., MontuoriA., & BarronA. (Eds.). (1997). Creators on creating: Awakening and cultivating the imaginative mind. New York, NY: Putnam.
4.
BrunerJ. S. (1962). The conditions of creativity. In GruberH., TerrellG., & WertheimerM. (Eds.), Contemporary approaches to creative thinking (pp. 1–30). New York, NY: Atherton.
5.
CropleyA. J. (1992). More ways than one: Fostering creativity. Norwood, NJ: Ablex.
6.
CsikszentmihalyiM. (1988). Society, culture, and person: A systems view of creativity. In SternbergR. J. (Ed.), The nature of creativity (pp. 325–339). New York, NY: Cambridge University Press.
7.
CsikszentmihalyiM. (1996). Creativity: Flow and the psychology of discovery and invention. New York, NY: Harper Collins.
8.
FeldhusenJ. F., & TreffingerD. J. (1985). Creative thinking and problem solving in gifted education. Dubuque, IA: Kendall Hunt Publishing Company.
9.
GardnerH. (1991). To open minds. New York, NY: Basic Books.
10.
GardnerH. (1993). Seven creators of the modern era. In BrockmanJ. (Ed.), Creativity (pp. 28–47). New York, NY: Simon & Schuster.
GetzelsJ. W., & CsikszentmihalyiM. (1975). From problem solving to problem finding. In TaylorI. A. & GetzelsJ. W. (Eds.), Perspectives in creativity (pp. 90–116). Chicago, IL: Aldine.
13.
HoutzJ. C. (1994). Creative problem solving in the classroom: Contributions of four psychological approaches. In RuncoM. A. (Ed.), Problem finding, problem solving, and creativity (pp. 153–173). Norwood, NJ: Ablex.
14.
JausovecN. (1994). Metacognition in creative problem solving. In RuncoM. A. (Ed.), Problem finding, problem solving, and creativity (pp. 77–95). Norwood, NJ: Ablex.
15.
LarssonL. (Ed.). (2002). Cultures of creativity: The centennial exhibition of the Nobel Prize (Rev. ed.). Canton, MA: Science History Publications.
16.
MacDormanK. F. (2005). Androids as an experimental apparatus: Why is there an uncanny valley and can we exploit it? In Cognitive Science 2005 Workshop: Toward Social Mechanisms of Android Science (pp. 106–118).
17.
McCloudS. (1993). Understanding comics. Amherst, MA: Kitchen Sink Press.
18.
MiyakeN., & OkitaS. Y. (2012). Robot facilitation as dynamic support for collaborative learning. In AalstJ., ThompsonK., JacobsonM. J., & ReimannP. (Eds.), Proceedings of the 10th International Conference of the Learning Sciences (ICLS) (Vol. 2, pp. 57–63), Sydney, Australia: University of Sydney: The International Conference of the Learning Sciences.
19.
NickersonR. S. (1999). Enhancing creativity. In SternbergR. J. (Ed.), Handbook of creativity (pp. 392–430). Cambridge, England: Cambridge University Press.
20.
OkitaS. Y. (2014a). The relative merits of transparency: Investigating situations that support the use of robotics in developing student learning adaptability across virtual and physical computing platforms. British Journal of Educational Technology, 45(5), 844–862.
21.
OkitaS. Y. (2014b). Learning from the folly of others: Learning to self-correct by monitoring the reasoning of virtual characters in a computer-supported mathematics learning environment. Computers and Education, 71, 257–278.
22.
OkitaS. Y., Ng-Thow-hingV., & SarvadevabhatlaR. K. (2011). Multimodal approach to affective human-robot interaction design with children. ACM Transactions on Interactive Intelligent Systems (TiiS), 1(1), 1–29.
23.
OkitaS. Y., & SchwartzD. L. (2006). Young children's understanding of animacy and entertainment robots. International Journal of Humanoid Robotics (IJHR), World Scientific, 3(3), 393–412.
24.
OkitaS. Y., & SchwartzD. L. (2013). Learning by teaching human pupils and teachable agents: The importance of recursive feedback. Journal of the Learning Sciences, 22(3), 375–412.
25.
RothenbergA. (1983). Janusian process and scientific creativity: The case of Niels Bohr. Contemporary Psychoanalysis, 19(1), 100–119.
26.
RuncoM. A. (1990). Implicit theories and ideational creativity. In RuncoM. A. & AlbertR. S. (Eds.), Theories of creativity (pp. 234–252). Newbury Park, CA: Sage Publications, Inc.
27.
RuncoM. A. (Ed.). (1994). Problem finding, problem solving, and creativity. Norwood, NJ: Ablex.
28.
SternbergR. J., & LubartT. I. (1995). Defying the crowd: Cultivating creativity in a culture of conformity. New York, NY: Free Press.
29.
WeisbergR. W. (1995). Case studies of creative thinking: Reproduction versus restructuring in the real world. In SmithS. M., WardT. B., & FinkeR. A. (Eds.), The creative cognition approach (pp. 53–72). Cambridge, MA: MIT Press.
