Abstract
This paper discusses how a dialogue-based tutoring system makes decisions to proactively scaffold students during conceptual discussions about physics. The tutor uses a student model to predict the likelihood that the student will answer the next question in a dialogue script correctly. Based on these predictions, the tutor will, step by step, choose the granularity at which the next step in the dialogue is discussed. The tutor attempts to pursue the discussion at the highest possible level, with the goal of helping the student achieve mastery, but with the constraint that the questions it asks are within the student’s ability to answer when appropriately supported; that is, the tutor aims to stay within its estimate of the student’s zone of proximal development for the targeted concepts. The scaffolding provided by the tutor is further adapted by adjusting the way the questions are expressed.
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Albacete, P., Jordan, P., Katz, S.: Is a dialogue-based tutoring system that emulates helpful co-constructed relations during human tutoring effective? In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M.Felisa (eds.) AIED 2015. LNCS (LNAI), vol. 9112, pp. 3–12. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19773-9_1
Cazden, C.: Peekaboo as An Instructional Model: Discourse Development at Home and at School. Stanford University Department of Linguistics, Palo Alto (1979)
Chi, M., Jordan, P., VanLehn, K.: When is tutorial dialogue more effective than step-based tutoring? In: Trausan-Matu, S., Boyer, K.E., Crosby, M., Panourgia, K. (eds.) ITS 2014. LNCS, vol. 8474, pp. 210–219. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07221-0_25
Chi, M., Koedinger, K.R., Gordon, G.J., Jordon, P., VanLehn, K.: Instructional factors analysis: a cognitive model for multiple instructional interventions. In: Pechenizkiy, M., Calders, T., Conati, C., Ventura, S., Romero, C., Stamper, J. (eds.) EDM 2011, pp. 61–70 (2011)
Chi, M.T., Siler, S.A., Jeong, H.: Can tutors monitor students’ understanding accurately? Cogn. Instr. 22(3), 363–387 (2004)
Chounta, I.-A., Albacete, P., Jordan, P., Katz, S., McLaren, Bruce M.: The “Grey Area”: a computational approach to model the zone of proximal development. In: Lavoué, É., Drachsler, H., Verbert, K., Broisin, J., Pérez-Sanagustín, M. (eds.) EC-TEL 2017. LNCS, vol. 10474, pp. 3–16. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66610-5_1
Chounta, I.A., McLaren, B.M., Albacete, P., Jordan, P., Katz, S.: Modeling the zone of proximal development with a computational approach. In: Hu, X., Barnes, T., Hershkovitz, A., Paquette, L. (eds.) EDM 2017, pp. 56–57 (2017)
Craig, S.D., Sullins, J., Witherspoon, A., Gholson, B.: The deep-level-reasoning-question effect: The role of dialogue and deep-level-reasoning questions during vicarious learning. Cogn. Instr. 24(4), 565–591 (2006)
Graesser, A.C., Lu, S., Jackson, G.T., Mitchell, H.H., Ventura, M., Olney, A., Louwerse, M.M.: AutoTutor: a tutor with dialogue in natural language. Behav. Rese. Methods Instrum. Comput. 36(2), 180–192 (2004)
Hume, G., Michael, J., Rovick, A., Evens, M.: Hinting as a tactic in one-on-one tutoring. J. Learn. Sci. 5(1), 23–49 (1996)
Jordan, P., Albacete, P., Katz, S.: Adapting step granularity in tutorial dialogue based on pretest scores. In: André, E., Baker, R., Hu, X., Rodrigo, Ma.Mercedes T., du Boulay, B. (eds.) AIED 2017. LNCS (LNAI), vol. 10331, pp. 137–148. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61425-0_12
Katz, S., Albacete, P., Jordan, P., Lusetich, D., Chounta, I.A., McLaren, B.M.: Operationalizing Contingent Tutoring in A Natural-Language Dialogue System. Nova Science Publishers (2018, submitted)
Katz, S., Albacete, P.: A tutoring system that simulates the highly interactive nature of human tutoring. J. Educ. Psychol. 105(4), 1126–1141 (2013)
van de Pol, J., Volman, M., Beishuizen, J.: Scaffolding in teacher-student interaction: a decade of research. Educ. Psychol. Rev. 22, 271–296 (2010)
Vygotsky, L.S.: Mind in society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge (1978)
Wood, D., Middleton, D.: A study of assisted problem-solving. Br. J. Psychol. 66(2), 181–191 (1975)
Wood, D., Wood, H.: Vygotsky, tutoring and learning. Oxford Rev. Educ. 22(1), 5–16 (1996)
Acknowledgments
We thank Sarah Birmingham and Scott Silliman. This research was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305A150155 to the University of Pittsburgh.
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Albacete, P., Jordan, P., Lusetich, D., Chounta, I.A., Katz, S., McLaren, B.M. (2018). Providing Proactive Scaffolding During Tutorial Dialogue Using Guidance from Student Model Predictions. In: Penstein Rosé, C., et al. Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science(), vol 10948. Springer, Cham. https://doi.org/10.1007/978-3-319-93846-2_4
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