TY - GEN
T1 - Variations of gaming behaviors across populations of students and across learning environments
AU - Paquette, Luc
AU - Baker, Ryan S.
N1 - Funding Information:
We would like to thank PSLC DataShop, Carnegie Learning and the ASSISTments team for providing us with access to student data. We would also like to thank support from NSF #DRL-1535340 and NSF #DRL-1252297.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Although gaming the system, a behavior in which students attempt to solve problems by exploiting help functionalities of digital learning environments, has been studied across multiple learning environments, little research has been done to study how (and whether) gaming manifests differently across populations of students and learning environments. In this paper, we study the differences in usage of 13 different patterns of actions associated with gaming the system by comparing their distribution across different populations of students using Cognitive Tutor Algebra and across students using one of three learning environments: Cognitive Tutor Algebra, Cognitive Tutor Middle School and ASSISTments. Results suggest that differences in gaming behavior are more strongly associated to the learning environments than to student populations and reveal different trends in how students use fast actions, similar answers and help request in different systems.
AB - Although gaming the system, a behavior in which students attempt to solve problems by exploiting help functionalities of digital learning environments, has been studied across multiple learning environments, little research has been done to study how (and whether) gaming manifests differently across populations of students and learning environments. In this paper, we study the differences in usage of 13 different patterns of actions associated with gaming the system by comparing their distribution across different populations of students using Cognitive Tutor Algebra and across students using one of three learning environments: Cognitive Tutor Algebra, Cognitive Tutor Middle School and ASSISTments. Results suggest that differences in gaming behavior are more strongly associated to the learning environments than to student populations and reveal different trends in how students use fast actions, similar answers and help request in different systems.
KW - Gaming the system
KW - Intelligent tutoring system
KW - Student populations
UR - http://www.scopus.com/inward/record.url?scp=85022183746&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-61425-0_23
DO - 10.1007/978-3-319-61425-0_23
M3 - Conference contribution
AN - SCOPUS:85022183746
SN - 9783319614243
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 274
EP - 286
BT - Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings
A2 - Andre, Elisabeth
A2 - Hu, Xiangen
A2 - Rodrigo, Ma. Mercedes T.
A2 - du Boulay, Benedict
A2 - Baker, Ryan
PB - Springer
T2 - 18th International Conference on Artificial Intelligence in Education, AIED 2017
Y2 - 28 June 2017 through 1 July 2017
ER -