Abstract
Since the development of the first digital computer in the 1940s, the notion of computer intelligence has received considerable attention from computer scientists, philosophers, and psychologists. The question of whether it is possible to create a computer program that possesses human intelligence has spurred much debate. Turing (1950) argued that computers are not capable of thinking and provided several theological, psychological, and sociological arguments in support of his position. To determine a computer program’s intelligence, Turing proposed several benchmark methods. One such method requires humans to decide whether they are interacting with an actual computer program or another human via computer mediation. According to Turing, a computer could be described as intelligent if it could deceive a human into believing that it was human. The two studies presented here were designed to determine whether AutoTutor could pass a variation of the Turing test, the Bystander Turing Test. The subsequent sections of this paper address the following: (1) the AutoTutor system, (2) the Bystander Turing Test, (3) the two empirical studies, and (4) the conclusions of the studies.
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References
Chi, M.T.H.: Constructing self explanations and scaffolded explanations in tutoring. Applied Cognitive Psycholog, 10(1996) S33–S49
Chi, M.T.H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R.: Self-explanations: How students study and use examples in learning to solve problems. Cognitive Scienc, 13 (1989) 145–182
Graesser, A.C., Hu, X., Susarla, S., Harter, D., Person, N.K., Louwerse, M., Olde, B., & the Tutoring Research Group: AutoTutor: An Intelligent Tutor and Conversational Tutoring Scaffold. Proceedings for the 10 th International Conference of Artificial Intelligence in Education San Antonio, TX (2001) 47–49
Graesser, A.C., Person, N.K., & Magliano, J.P.: Collaborative dialogue patterns in naturalistic one-to-one tutoring sessions. Applied Cognitive Psychology 9 (1995) 1–28
Graesser, A.C., Person, N.K., Harter, D., & the Tutoring Research Group: Tactics in tutoring in AutoTutor. In the ITS 2000 Proceedings of the Workshop on Modeling Human Teaching Tactics and Strategies Montreal, Canada (2000) 49–57
Graesser, A.C., Wiemer-Hastings, K., Wiemer-Hastings, P., Kreuz, R., & TRG: AutoTutor: A simulation of a human tutor. Journal of Cognitive Systems Research 1(1999) 35–51
Graesser, A.C., Wiemer-Hastings, P., Wiemer-Hastings, K., Harter, D., Person, N., & the Tutoring Research Group: Using latent semantic analysis to evaluate the contributions of students in AutoTutor. Interactive Learning Environments 8 (2000) 129–148
Person, N.K., & Graesser, A.C.: Evolution of discourse in cross-age tutoring. In A. M. O’Donnell and A. King (Eds.), Cognitive perspectives on peer learning Mahwah, NJ: Erlbaum (1999) 69–86
Person, N.K., Graesser, A.C., & the Tutoring Research Group: Designing AutoTutor to be an effective conversational partner. In the Proceedings for the 4 th International Conference of the Learning Sciences Ann Arbor, MI (2000) 246–253
Person, N.K., Graesser, A.C., Bautista, L., Mathews, E.C., & the Tutoring Research Group: Evaluating Student Learning Gains in Two Versions of AutoTutor. In J.D. Moore, C.L. Redfield, & W.L. Johnson (Eds.) Artificial intelligence in education: AI-ED in the wired and wireless future Amsterdam, IOS Press (2001) 286–293
Person, N.K., Graesser, A.C., Harter, D., Mathews, E.C., & the Tutoring Research Group: Dialog move generation and conversation management in AutoTutor. Proceedings of the AAAI Fall Symposium: Building Dialogue Systems for Tutorial Applications Falmouth, MA: AAAI Press (2000) 45–51
Person, N.K., Graesser, A.C., Kreuz, R.J., Pomeroy, V., & the Tutoring Research Group: Simulating human tutor dialog moves in AutoTutor. International Journal of Artificial Intelligence in Education 12 (2001b) 23–29
Person, N.K., Klettke, B., Link, K., Kreuz, R.J., & the Tutoring Research Group: The integration of affective responses into AutoTutor. Proceedings of the International Workshop on Affect in Interactions Siena, Italy (1999) 167–178
Turing, A.M.: Computing Machinery and Intelligence. In E.A. Feigenbaum & J. Feldman (Eds.) Computers and thought. New York: McGraw-Hill (1950)
Wiemer-Hastings, P., Graesser, A.C., Harter, D., and the Tutoring Research Group: The foundations and architecture of AutoTutor. Proceedings of the 4th International Conference on Intelligent Tutoring Systems Berlin, Germany: Springer-Verlag (1998) 334–343
Wiemer-Hastings, P., Wiemer-Hastings, K., and Graesser, A.: Improving an intelligent tutor’s comprehension of students with Latent Semantic Analysis. Artificial Intelligence in Education Amsterdam: IOS Press (1999) 535–542
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© 2002 Springer-Verlag Berlin Heidelberg
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The Tutoring Research Group., Person, N., Graesser, A.C. (2002). Human or Computer? AutoTutor in a Bystander Turing Test. In: Cerri, S.A., Gouardères, G., Paraguaçu, F. (eds) Intelligent Tutoring Systems. ITS 2002. Lecture Notes in Computer Science, vol 2363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47987-2_82
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DOI: https://doi.org/10.1007/3-540-47987-2_82
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