Abstract
Open-ended educational systems such as games have been broadly under investigation in recent years due to their potential in making learning enjoyable and offering the adaptive pedagogy of intelligent tutoring systems. The most important challenge in building such systems is to predict individual behavior which results in better understanding of the learning process. Model-based methods are a standard way to learn individual behavior in highly-structured systems. However, these methods heavily rely on expert domain knowledge. Since adaptive educational games may create a huge space of actions, applying model-based approaches in these systems are very difficult. In order to counter this difficulty, researchers utilize data-driven methods that are not dependent on expert domain knowledge to learn a subject's behavior based on a history of user interactions. Due to the fact that the potential of applying data-driven approaches in adaptive educational games is still missing, the goal of this report is to cater a survey in the area in order to ease comprehending the state of the art.
| Original language | English |
|---|---|
| Title of host publication | Proceeding - 2016 2nd International Conference on Science in Information Technology, ICSITech 2016: Information Science for Green Society and Environment |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 291-295 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509017218 |
| DOIs | |
| Publication status | Published - 2017 Feb 13 |
| Event | 2nd International Conference on Science in Information Technology, ICSITech 2016 - Balikpapan, Indonesia Duration: 2016 Oct 26 → 2016 Oct 27 |
Other
| Other | 2nd International Conference on Science in Information Technology, ICSITech 2016 |
|---|---|
| Country | Indonesia |
| City | Balikpapan |
| Period | 16/10/26 → 16/10/27 |
Fingerprint
Keywords
- data-driven approaches
- educational games
- user modeling formatting
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
- Signal Processing
Cite this
A survey on data-driven approaches in educational games. / Hooshyar, Danial; Lee, Chanhee; Lim, Heui Seok.
Proceeding - 2016 2nd International Conference on Science in Information Technology, ICSITech 2016: Information Science for Green Society and Environment. Institute of Electrical and Electronics Engineers Inc., 2017. p. 291-295 7852650.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A survey on data-driven approaches in educational games
AU - Hooshyar, Danial
AU - Lee, Chanhee
AU - Lim, Heui Seok
PY - 2017/2/13
Y1 - 2017/2/13
N2 - Open-ended educational systems such as games have been broadly under investigation in recent years due to their potential in making learning enjoyable and offering the adaptive pedagogy of intelligent tutoring systems. The most important challenge in building such systems is to predict individual behavior which results in better understanding of the learning process. Model-based methods are a standard way to learn individual behavior in highly-structured systems. However, these methods heavily rely on expert domain knowledge. Since adaptive educational games may create a huge space of actions, applying model-based approaches in these systems are very difficult. In order to counter this difficulty, researchers utilize data-driven methods that are not dependent on expert domain knowledge to learn a subject's behavior based on a history of user interactions. Due to the fact that the potential of applying data-driven approaches in adaptive educational games is still missing, the goal of this report is to cater a survey in the area in order to ease comprehending the state of the art.
AB - Open-ended educational systems such as games have been broadly under investigation in recent years due to their potential in making learning enjoyable and offering the adaptive pedagogy of intelligent tutoring systems. The most important challenge in building such systems is to predict individual behavior which results in better understanding of the learning process. Model-based methods are a standard way to learn individual behavior in highly-structured systems. However, these methods heavily rely on expert domain knowledge. Since adaptive educational games may create a huge space of actions, applying model-based approaches in these systems are very difficult. In order to counter this difficulty, researchers utilize data-driven methods that are not dependent on expert domain knowledge to learn a subject's behavior based on a history of user interactions. Due to the fact that the potential of applying data-driven approaches in adaptive educational games is still missing, the goal of this report is to cater a survey in the area in order to ease comprehending the state of the art.
KW - data-driven approaches
KW - educational games
KW - user modeling formatting
UR - http://www.scopus.com/inward/record.url?scp=85016230539&partnerID=8YFLogxK
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U2 - 10.1109/ICSITech.2016.7852650
DO - 10.1109/ICSITech.2016.7852650
M3 - Conference contribution
SP - 291
EP - 295
BT - Proceeding - 2016 2nd International Conference on Science in Information Technology, ICSITech 2016: Information Science for Green Society and Environment
PB - Institute of Electrical and Electronics Engineers Inc.
ER -