Exploring Robot's Playing Strategy with a Language Learning Robot Companion

Talgat Tursynbekov; Kairat Balkibekov; Alisher Asatarov; Anara Sandygulova

doi:10.1145/3173386.3177086

Exploring Robot's Playing Strategy with a Language Learning Robot Companion

Talgat Tursynbekov, Kairat Balkibekov, Alisher Asatarov, Anara Sandygulova

Department of Robotics and Mechatronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents a preliminary study exploring playing strategy of a robot and the way it can affect a learning outcome of young adults. We developed a social robot that plays the role of a learning companion for a foreign language. We conducted a preliminary study where we explored two robot playing strategies, always-winning and always-losing, on the learning outcomes of the participant. In addition, we also wanted to find out whether the personality of participants might have an effect on their learning performance. This pilot study was conducted with 20 participants aged 17-25 years old. Our preliminary findings suggest that extroverts learn more when they win the robot while introverts learn more when the game ends in a draw.

Original language	English
Title of host publication	HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction
Publisher	IEEE Computer Society
Pages	261-262
Number of pages	2
ISBN (Electronic)	9781450356152
DOIs	https://doi.org/10.1145/3173386.3177086
Publication status	Published - Mar 1 2018
Event	13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018 - Chicago, United States Duration: Mar 5 2018 → Mar 8 2018

Conference

Conference	13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018
Country	United States
City	Chicago
Period	3/5/18 → 3/8/18

Fingerprint

Keywords

adaptive strategies
educational robotics
human-robot interaction
social robotics

ASJC Scopus subject areas

Artificial Intelligence
Human-Computer Interaction
Electrical and Electronic Engineering

Cite this

Tursynbekov, T., Balkibekov, K., Asatarov, A., & Sandygulova, A. (2018). Exploring Robot's Playing Strategy with a Language Learning Robot Companion. In HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (pp. 261-262). IEEE Computer Society. https://doi.org/10.1145/3173386.3177086

Exploring Robot's Playing Strategy with a Language Learning Robot Companion. / Tursynbekov, Talgat; Balkibekov, Kairat; Asatarov, Alisher; Sandygulova, Anara.

HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, 2018. p. 261-262.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tursynbekov, T, Balkibekov, K, Asatarov, A & Sandygulova, A 2018, Exploring Robot's Playing Strategy with a Language Learning Robot Companion. in HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, pp. 261-262, 13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018, Chicago, United States, 3/5/18. https://doi.org/10.1145/3173386.3177086

@inproceedings{01d57f250da548a4ac23bfe5fdf07c2b,

title = "Exploring Robot's Playing Strategy with a Language Learning Robot Companion",

abstract = "This paper presents a preliminary study exploring playing strategy of a robot and the way it can affect a learning outcome of young adults. We developed a social robot that plays the role of a learning companion for a foreign language. We conducted a preliminary study where we explored two robot playing strategies, always-winning and always-losing, on the learning outcomes of the participant. In addition, we also wanted to find out whether the personality of participants might have an effect on their learning performance. This pilot study was conducted with 20 participants aged 17-25 years old. Our preliminary findings suggest that extroverts learn more when they win the robot while introverts learn more when the game ends in a draw.",

keywords = "adaptive strategies, educational robotics, human-robot interaction, social robotics",

author = "Talgat Tursynbekov and Kairat Balkibekov and Alisher Asatarov and Anara Sandygulova",

year = "2018",

month = mar

day = "1",

doi = "10.1145/3173386.3177086",

language = "English",

pages = "261--262",

booktitle = "HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction",

publisher = "IEEE Computer Society",

address = "United States",

note = "13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018 ; Conference date: 05-03-2018 Through 08-03-2018",

}

TY - GEN

T1 - Exploring Robot's Playing Strategy with a Language Learning Robot Companion

AU - Tursynbekov, Talgat

AU - Balkibekov, Kairat

AU - Asatarov, Alisher

AU - Sandygulova, Anara

PY - 2018/3/1

Y1 - 2018/3/1

N2 - This paper presents a preliminary study exploring playing strategy of a robot and the way it can affect a learning outcome of young adults. We developed a social robot that plays the role of a learning companion for a foreign language. We conducted a preliminary study where we explored two robot playing strategies, always-winning and always-losing, on the learning outcomes of the participant. In addition, we also wanted to find out whether the personality of participants might have an effect on their learning performance. This pilot study was conducted with 20 participants aged 17-25 years old. Our preliminary findings suggest that extroverts learn more when they win the robot while introverts learn more when the game ends in a draw.

AB - This paper presents a preliminary study exploring playing strategy of a robot and the way it can affect a learning outcome of young adults. We developed a social robot that plays the role of a learning companion for a foreign language. We conducted a preliminary study where we explored two robot playing strategies, always-winning and always-losing, on the learning outcomes of the participant. In addition, we also wanted to find out whether the personality of participants might have an effect on their learning performance. This pilot study was conducted with 20 participants aged 17-25 years old. Our preliminary findings suggest that extroverts learn more when they win the robot while introverts learn more when the game ends in a draw.

KW - adaptive strategies

KW - educational robotics

KW - human-robot interaction

KW - social robotics

UR - http://www.scopus.com/inward/record.url?scp=85045265166&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85045265166&partnerID=8YFLogxK

U2 - 10.1145/3173386.3177086

DO - 10.1145/3173386.3177086

M3 - Conference contribution

AN - SCOPUS:85045265166

SP - 261

EP - 262

BT - HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction

PB - IEEE Computer Society

T2 - 13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018

Y2 - 5 March 2018 through 8 March 2018

ER -

Access to Document

10.1145/3173386.3177086