Feasibility of learning by observing in collaborative learning with robots which changes the learning method

被引:0
|
作者
Jimenez F. [1 ]
Kanoh M. [2 ]
Yoshikawa T. [1 ]
Furuhashi T.
机构
[1] Graduate School of Engineering, Nagoya University
[2] School of Engineering, Chukyo University
关键词
Collaborative learning; Human-robot-interaction; Learning by observing; Robot;
D O I
10.1527/tjsai.D-G51
中图分类号
学科分类号
摘要
This paper sought to examine how behavior of a robot can prompt learning by observing in collaborative learning. The robot learns while solving a problem issued by an English vocabulary learning system with a human learner. The learning system presents English words in example sentences and uses a scaffolding function that helps the learner guess the meaning of English words in the example sentence upon a user request. The robot was designed to solve the questions by using scaffolding function and could not answer correctly at beginning. However, the robot change its question-answering method by guessing the meanings of English words in example sentences and improve its accuracy as learning progressed. This behavior of robot can prompt learners to learn by observing in collaborative learning. Ten college students with low level English learned using the English vocabulary learning system with robot for two months and were videoed during that time to see how they learned. We found that learners learned the English vocabulary by using scaffolding function at beginning. However, learners changed their learning method form using scaffolding function to guessing the meanings of English words in English sentences by learning progress. This suggests that robot, which changes the question-solving method to a more effective one and increases its accuracy rate as learning progress, prompts learners to learning by observing in collaborative learning and change their learning method to the more effective one. This learning by observing indicates that learners learn how to guess the meanings of English words in English sentences by observing the robot’s question-solving and speaking. However, the robot does not prompt some learners to learning by observing because they feel lousy that the robot answers the question and improves its accuracy rate, so they ignore what the robot says. Additionally, learners interest in robot decrease when robot performs the same action. © 2017, Japanese Society for Artificial Intelligence. All rights reserved.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Collaborative Learning
    Bauer, Claudia
    DANCE MAGAZINE, 2017, 91 (01): : 136 - 137
  • [42] COLLABORATIVE LEARNING
    BRUFFEE, KA
    TECHNOLOGY REVIEW, 1993, 96 (05): : 7 - 8
  • [43] A Graph Based Data Mining Method for Collaborative Learning Space in Learning Commons
    Okamoto, Kazushi
    Asanuma, Hitoshi
    Kawamoto, Kazuhiko
    2014 WORLD AUTOMATION CONGRESS (WAC): EMERGING TECHNOLOGIES FOR A NEW PARADIGM IN SYSTEM OF SYSTEMS ENGINEERING, 2014,
  • [44] Introduction to Machine Learning with Robots and Playful Learning
    Olari, Viktoriya
    Cvejoski, Kostadin
    Eide, Oyvind
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 15630 - 15639
  • [45] E-learning as a method which supports the process of learning An invitation for the conference
    Maciejewicz, Anna
    Cieszynska, Mariola
    E-MENTOR, 2006, (02): : 29 - 30
  • [46] A Learning Method for Product Analysis in Product Design Learning Method of Product Analysis Utilizing Collaborative Learning and a List of Analysis Items
    Lin, Haifu
    Kato, Hiroshi
    Toya, Takeshi
    HUMAN INTERFACE AND THE MANAGEMENT OF INFORMATION: INFORMATION AND KNOWLEDGE DESIGN AND EVALUATION, PT I, 2014, 8521 : 503 - 513
  • [47] Collaborative learning environment which enforces students to induce ideas
    Kojiri, T
    Watanabe, T
    INTELLIGENT TUTORING SYSTEMS, PROCEEDINGS, 2000, 1839 : 657 - 657
  • [48] Collaborative Learning Method for Natural Image Captioning
    Wang, Rongzhao
    Liu, Libo
    DATA SCIENCE (ICPCSEE 2022), PT I, 2022, 1628 : 249 - 261
  • [49] Architecture of collaborative filtering system which promotes explorative learning
    Okamoto, T
    Miyahara, K
    PROCEEDINGS OF ICCE'98, VOL 1 - GLOBAL EDUCATION ON THE NET, 1998, : 453 - 458
  • [50] COLLABORATIVE METHOD FOR INCREMENTAL LEARNING ON CLASSIFICATION AND GENERATION
    Kim, Byungju
    Lee, Jaeyoung
    Kim, Kyungsu
    Kim, Sungjin
    Kim, Junmo
    2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2019, : 390 - 394