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Can a teachable agent influence how students respond to competition in an educational game?

Sjödén, Björn LU ; Lind, Mats and Silvervarg, Annika (2017) 18th International Conference on Artificial Intelligence in Education, AIED 2017 In Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings 10331 LNAI. p.347-358
Abstract

Learning in educational games is often associated with some form of competition. We investigated how students responded to winning or losing in an educational math game, with respect to playing with or without a Teachable Agent (TA). Students could choose between game modes in which the TA took a more passive or active role, or let the TA play a game entirely on its own. Based on the data logs from 3983 games played by 163 students (age 10–11), we analyzed data on students’ persistence, challenge-seeking and performance during gameplay. Results indicated that students showed greater persistence when playing together with the TA, by more often repeating a lost game with the TA, than a lost game after playing alone. Students’... (More)

Learning in educational games is often associated with some form of competition. We investigated how students responded to winning or losing in an educational math game, with respect to playing with or without a Teachable Agent (TA). Students could choose between game modes in which the TA took a more passive or active role, or let the TA play a game entirely on its own. Based on the data logs from 3983 games played by 163 students (age 10–11), we analyzed data on students’ persistence, challenge-seeking and performance during gameplay. Results indicated that students showed greater persistence when playing together with the TA, by more often repeating a lost game with the TA, than a lost game after playing alone. Students’ challenge-seeking, by increasing the difficulty level, was greater following a win than following a loss, especially after the TA won on its own. Students’ gameplay performance was unaffected by their TA winning or losing but was, unexpectedly, slightly worse following a win by the student alone. We conclude that engaging a TA can make students respond more productively to both winning and losing, depending on the particular role the TA takes in the game. These results may inform more specific hypotheses as to the differential effects of competing and collaborating in novel, AI-supported social constellations, such as with TAs, on students’ motivation and ego-involvement in educational games.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Competition, Educational game, Social influence, Teachable agent
in
Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings
volume
10331 LNAI
pages
12 pages
publisher
Springer Verlag
conference name
18th International Conference on Artificial Intelligence in Education, AIED 2017
external identifiers
  • scopus:85022190414
ISSN
03029743
16113349
ISBN
9783319614243
DOI
10.1007/978-3-319-61425-0_29
language
English
LU publication?
yes
id
4f69489c-6c80-4757-bc1f-98b9c37b19fc
date added to LUP
2017-07-24 15:12:31
date last changed
2017-07-24 15:12:31
@inproceedings{4f69489c-6c80-4757-bc1f-98b9c37b19fc,
  abstract     = {<p>Learning in educational games is often associated with some form of competition. We investigated how students responded to winning or losing in an educational math game, with respect to playing with or without a Teachable Agent (TA). Students could choose between game modes in which the TA took a more passive or active role, or let the TA play a game entirely on its own. Based on the data logs from 3983 games played by 163 students (age 10–11), we analyzed data on students’ persistence, challenge-seeking and performance during gameplay. Results indicated that students showed greater persistence when playing together with the TA, by more often repeating a lost game with the TA, than a lost game after playing alone. Students’ challenge-seeking, by increasing the difficulty level, was greater following a win than following a loss, especially after the TA won on its own. Students’ gameplay performance was unaffected by their TA winning or losing but was, unexpectedly, slightly worse following a win by the student alone. We conclude that engaging a TA can make students respond more productively to both winning and losing, depending on the particular role the TA takes in the game. These results may inform more specific hypotheses as to the differential effects of competing and collaborating in novel, AI-supported social constellations, such as with TAs, on students’ motivation and ego-involvement in educational games.</p>},
  author       = {Sjödén, Björn and Lind, Mats and Silvervarg, Annika},
  booktitle    = {Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings},
  isbn         = {9783319614243},
  issn         = {03029743},
  keyword      = {Competition,Educational game,Social influence,Teachable agent},
  language     = {eng},
  pages        = {347--358},
  publisher    = {Springer Verlag},
  title        = {Can a teachable agent influence how students respond to competition in an educational game?},
  url          = {http://dx.doi.org/10.1007/978-3-319-61425-0_29},
  volume       = {10331 LNAI},
  year         = {2017},
}