Abstract
The current study investigates the relation between personalizable feature use, attitudes, and in-system performance in the context of the game-based system, iSTART-ME. This analysis focuses on a subset (n=40) of a larger study (n=126) conducted with high school students. The results revealed a positive relation between students’ frequency of interactions with personalizable features and their self-reported engagement and perceived system control. Students who frequently interacted with personalizable features also demonstrated better overall in-system performance compared to students who interacted with these features less often. The current paper adds to the growing literature supporting the potential positive impact that personalizable features have on students’ attitudes and performance in adaptive learning environments.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013 |
| Editors | Sidney K. D'Mello, Rafael A. Calvo, Andrew Olney |
| Publisher | International Educational Data Mining Society |
| ISBN (Electronic) | 9780983952527 |
| State | Published - Jan 1 2013 |
| Event | 6th International Conference on Educational Data Mining, EDM 2013 - Memphis, United States Duration: Jul 6 2013 → Jul 9 2013 |
Publication series
| Name | Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013 |
|---|
Conference
| Conference | 6th International Conference on Educational Data Mining, EDM 2013 |
|---|---|
| Country | United States |
| City | Memphis |
| Period | 7/6/13 → 7/9/13 |
Fingerprint
Keywords
- Attitudes
- Game-based features
- Off-task behaviors
- Personalization
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems
Cite this
Investigating the effects of off-task personalization on in-system performance and attitudes within a game-based environment. / Snow, Erica L.; Jackson, G. Tanner; Varner, Laura K.; McNamara, Danielle.
Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013. ed. / Sidney K. D'Mello; Rafael A. Calvo; Andrew Olney. International Educational Data Mining Society, 2013. (Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Investigating the effects of off-task personalization on in-system performance and attitudes within a game-based environment
AU - Snow, Erica L.
AU - Jackson, G. Tanner
AU - Varner, Laura K.
AU - McNamara, Danielle
PY - 2013/1/1
Y1 - 2013/1/1
N2 - The current study investigates the relation between personalizable feature use, attitudes, and in-system performance in the context of the game-based system, iSTART-ME. This analysis focuses on a subset (n=40) of a larger study (n=126) conducted with high school students. The results revealed a positive relation between students’ frequency of interactions with personalizable features and their self-reported engagement and perceived system control. Students who frequently interacted with personalizable features also demonstrated better overall in-system performance compared to students who interacted with these features less often. The current paper adds to the growing literature supporting the potential positive impact that personalizable features have on students’ attitudes and performance in adaptive learning environments.
AB - The current study investigates the relation between personalizable feature use, attitudes, and in-system performance in the context of the game-based system, iSTART-ME. This analysis focuses on a subset (n=40) of a larger study (n=126) conducted with high school students. The results revealed a positive relation between students’ frequency of interactions with personalizable features and their self-reported engagement and perceived system control. Students who frequently interacted with personalizable features also demonstrated better overall in-system performance compared to students who interacted with these features less often. The current paper adds to the growing literature supporting the potential positive impact that personalizable features have on students’ attitudes and performance in adaptive learning environments.
KW - Attitudes
KW - Game-based features
KW - Off-task behaviors
KW - Personalization
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M3 - Conference contribution
AN - SCOPUS:84919895343
T3 - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
BT - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
A2 - D'Mello, Sidney K.
A2 - Calvo, Rafael A.
A2 - Olney, Andrew
PB - International Educational Data Mining Society
ER -