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Learning Effects of Robots Teaching Based on Cognitive Apprenticeship Theory
Author(s) -
Kenya Miyauchi,
Felix Jimenez,
Tomohiro Yoshikawa,
Takeshi Furuhashi,
Masayoshi Kanoh
Publication year - 2020
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2020.p0101
Subject(s) - cognitive apprenticeship , apprenticeship , robot , computer science , cognition , mathematics education , experiential learning , learning theory , artificial intelligence , psychology , linguistics , philosophy , neuroscience
In recent years, educational support robots that assist learners have attracted attention. The main role of teacher-type robots in previous research has been to teach students how to solve problems and to explain learning material. Under such conditions, students may not learn the material adequately due to their reliance on the support of the robot; this paper utilizes the cognitive apprenticeship theory in order to prevent this problem. The cognitive apprenticeship theory asserts that the support provided to a student should change according to the student’s learning situation. Previous studies have reported that pedagogy based on the cognitive apprenticeship theory can improve students’ learning skills. Therefore, we hypothesize that students’ learning will improve when robots teach them how to solve questions based on the cognitive apprenticeship theory. In this paper, we investigate the learning effects of robot teaching based on the cognitive apprenticeship theory in collaborative learning with junior high-school and university students. The results of this experiment suggest that collaborative learning with robots that employ the cognitive apprenticeship theory improves the learning of high-school and university students.

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