Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics

Autor/inn/en	Katz, Sandra; Albacete, Patricia; Chounta, Irene-Angelica; Jordan, Pamela; McLaren, Bruce M.; Zapata-Rivera, Diego
Titel	Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics
Quelle	In: International Journal of Artificial Intelligence in Education, 31 (2021) 3, S.397-445 (49 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.1007/s40593-020-00226-y
Schlagwörter	Physics; Science Instruction; Pretests Posttests; Scores; Intelligent Tutoring Systems; Pilot Projects; Teaching Methods; Problem Solving; Dialogs (Language); High School Students; Comparative Analysis; Models; Prior Learning; Intervention; Instructional Effectiveness + Suchen Sie Ihr Suchwort? Physik; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Intelligentes Tutorsystem; Pilot project; Modellversuch; Pilotprojekt; Teaching method; Lehrmethode; Unterrichtsmethode; Problemlösen; Dialog; Dialogs; Dialogue; Dialogues; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Analogiemodell; Vorkenntnisse; Unterrichtserfolg
Abstract	Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However, considerably less attention has been paid to using a student model to personalize instruction in tutorial dialogue systems (TDSs)--ITSs that engage students in natural-language, conceptual discussions. This paper describes Rimac, a TDS that tightly couples student modelling with tutorial dialogues about conceptual physics. Rimac is distinct from other TDSs insofar as it dynamically builds a persistent student model that guides reactive and proactive decision making in order to provide adaptive instruction. An initial pilot study set in high school physics classrooms compared a control version of Rimac without a student model with an experimental version that implemented a "poor man's student model"; that is, the model was initialized using students' pretest scores but not updated further. Both low and high prior knowledge students showed significant pretest to posttest learning gains. However, high prior knowledge students who used the experimental version of Rimac learned more efficiently than high prior knowledge students who used the control version. Specifically, high prior knowledge students who used the student model driven tutor took less time to complete the intervention but learned a similar amount as students who used the control version. A subsequent study found that both high and low prior knowledge students learned more efficiently from a version of the tutor that dynamically updates its student model during dialogues than from a control version that included the static "poor man's student model." We discuss future work needed to improve the performance of Rimac's student model and to integrate TDSs in the classroom. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01