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 | |
| 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 |
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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
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
}
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
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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
ER -