@inproceedings{e4ba37c942704ff2b474412f0c749b77,
title = "Robot as a Ventriloquist Doll in a Virtual Situational Learning Environment to Facilitate Learning Through Self-Dialogue",
abstract = "One of the ways of thinking about how to finish the learning task is through self-dialogue. Doing so enables learners to ask themselves what should they do and evaluate whether it is appropriate from another point of view. However, learners might have difficulties imagining the scenario and interacting with an imaginary person. They may need a scaffolding tool or a person as a partner to practice the self-dialogue. Besides, the ventriloquist phenomenon in education has been noted as beneficial for learning as it could make the learners understands the idea through dialogue. This study proposed a learning approach that allows the learners to use a robot as a ventriloquist doll for practicing self-dialogue and knowledge application to enhance their learning effectiveness. The experiment was conducted by participating 104 undergraduate learners who enrolled in a Japanese Hospitality Management course. The results showed that the approach used a ventriloquist robot to facilitate learning through self-dialogue exhibited significant effects on motivation, anxiety, and better learning outcomes. This study provides a novel area of insight into the use of robots in learning, by integrating digital technology with pedagogical approaches to create an immersive intelligent learning environment and offer a self-dialogue mechanism to foster collaborative learning tasks.",
keywords = "Collaborative Learning, Human-Robot Interaction, Robot for Learning, Scaffolding Tool, Self-Dialogue, Ventriloquist, Virtual Situational Learning Environment",
author = "Hakim, {Vando Gusti Al} and Yang, {Su Hang} and Mahesh Liyanawatta and Wang, {Jen Hang} and Ku, {Yung Han} and Zhuang, {Yung Yu} and Chen, {Gwo Dong}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 22nd International Conference on Advanced Learning Technologies, ICALT 2022 ; Conference date: 01-07-2022 Through 04-07-2022",
year = "2022",
doi = "10.1109/ICALT55010.2022.00043",
language = "???core.languages.en_GB???",
series = "Proceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "117--121",
editor = "Maiga Chang and Nian-Shing Chen and Mihai Dascalu and Sampson, {Demetrios G} and Ahmed Tlili and Stefan Trausan-Matu",
booktitle = "Proceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022",
}