Improving Artificial Teachers by Considering How People Learn and Forget

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaKonferenssiesitysScientificvertaisarvioitu

Abstrakti

The paper presents a novel model-based method for intelligent tutoring, with particular emphasis on the problem of selecting teaching interventions in interaction with humans. Whereas previous work has focused on either personalization of teaching or optimization of teaching intervention sequences, the proposed individualized model-based planning approach represents convergence of these two lines of research. Model-based planning picks the best interventions via interactive learning of a user memory model’s parameters. The approach is novel in its use of a cognitive model that can account for several key individual- and material-specific characteristics related to recall/forgetting, along with a planning technique that considers users’ practice schedules. Taking a rule-based approach as a baseline, the authors evaluated the method’s benefits in a controlled study of artificial teaching in second-language vocabulary learning (N = 53).
AlkuperäiskieliEnglanti
Sivut445-453
Sivumäärä9
TilaHyväksytty/In press - 2021
OKM-julkaisutyyppiEi oikeutettu
TapahtumaInternational Conference on Intelligent User Interfaces - Virtual, Online, College Station, Yhdysvallat
Kesto: 13 huhtikuuta 202117 huhtikuuta 2021
Konferenssinumero: 26

Conference

ConferenceInternational Conference on Intelligent User Interfaces
LyhennettäIUI
MaaYhdysvallat
KaupunkiCollege Station
Ajanjakso13/04/202117/04/2021

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