Why Students Engage in “Gaming the System” Behavior in Interactive Learning Environments

In recent years there has been increasing interest in the phenomena of " gaming the system, " where a learner attempts to succeed in an educational environment by exploiting properties of the system's help and feedback rather than by attempting to learn the material. Developing environments that respond constructively and effectively to gaming depends upon understanding why students choose to game. In this article , we present three studies, conducted with two different learning environments, which present evidence on which student behaviors, motivations, and emotions are associated with the choice to game the system. We also present a fourth study to determine how teachers' perspectives on gaming behavior are similar to, and different from, researchers' perspectives and the data from our studies. We discuss what motivational and attitudinal patterns are associated with gaming behavior across studies, and what the implications are for the design of interactive learning environment.

[1]  L. Frank The Society for Research in Child Development , 1935 .

[2]  S. Sarason,et al.  Anxiety in elementary school children : a report of research , 1960 .

[3]  D. Harnisch Development of a Shorter, More Reliable, and More Valid Measure of Test Motivation. , 1980 .

[4]  Brian H. Spitzberg,et al.  Trait versus state: A comparison of dispositional and situational measures of interpersonal communication competence , 1983 .

[5]  P. Costa,et al.  Personality in adulthood , 1990 .

[6]  Ulrich Schiefele,et al.  Interest, Learning, and Motivation , 1991 .

[7]  F. Rhodewalt,et al.  Conceptions of Ability, Achievement Goals, and Individual Differences in Self‐Handicapping Behavior: On the Application of Implicit Theories , 1994 .

[8]  F. Paas,et al.  Variability of Worked Examples and Transfer of Geometrical Problem-Solving Skills: A Cognitive-Load Approach , 1994 .

[9]  J. Pearce Abnormalities of personality— Within and beyond the realm of treatment , 1995 .

[10]  J. Schofield Computers and classroom culture , 1995 .

[11]  E. Maris Psychometric latent response models , 1995 .

[12]  James R. Lewis,et al.  IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use , 1995, Int. J. Hum. Comput. Interact..

[13]  John R. Anderson,et al.  Cognitive Tutors: Lessons Learned , 1995 .

[14]  Middle School Students' Perceptions of Math and Science Abilities and Related Careers. , 1995 .

[15]  M. Lepper,et al.  Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice. , 1996 .

[16]  D. Stipek,et al.  Children's beliefs about intelligence and school performance. , 1996 .

[17]  Neil Selwyn,et al.  Students' attitudes toward computers: Validation of a computer attitude scale for 16-19 education , 1997, Comput. Educ..

[18]  A. Arbreton Student goal orientation and help-seeking strategy use. , 1998 .

[19]  C. Dweck,et al.  Praise for intelligence can undermine children's motivation and performance. , 1998, Journal of personality and social psychology.

[20]  S. Karabenick Strategic help seeking : implications for learning and teaching , 1998 .

[21]  D. Wood,et al.  Help seeking, learning and contingent tutoring , 1999, Comput. Educ..

[22]  C. Sansone,et al.  Self-regulating interest: the moderating role of hardiness and conscientiousness. , 1999, Journal of personality.

[23]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[24]  D. Wood Self-theories: Their Role in Motivation, Personality and Development. By Carol S. Dweck. Psychology Press, Hove, 1999. pp. 195. £29.95 (hb). , 2000 .

[25]  G. Parker,et al.  A question of style: refining the dimensions of personality disorder style. , 2001, Journal of personality disorders.

[26]  Preston G. Smith The art of innovation: lessons in creativity from IDEO, America’s leading design firm: Tom Kelley with Jonathan Littman; New York: Doubleday, 2001, 308 + xii pages, $26.00 , 2002 .

[27]  Catherine G. Frantom,et al.  Measure Development: The Children's Attitudes toward Technology Scale (CATS) , 2002 .

[28]  Jack Mostow,et al.  Experimentally augmenting an intelligent tutoring system with human-supplied capabilities: adding human-provided emotional scaffolding to an automated reading tutor that listens , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

[29]  Jack Mostow,et al.  A La Recherche du Temps Perdu, or As Time Goes By: Where Does the Time Go in a Reading Tutor That Listens? , 2002, Intelligent Tutoring Systems.

[30]  R. Hu Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) , 2003 .

[31]  Antonija Mitrovic,et al.  Scaffolding and Fading Problem Selection in SQL-Tutor , 2003 .

[32]  Rose Luckin,et al.  Goal achievement orientation in the design of an ILE , 2004 .

[33]  Ryan Shaun Joazeiro de Baker,et al.  Off-task behavior in the cognitive tutor classroom: when students "game the system" , 2004, CHI.

[34]  Morten Misfeldt,et al.  Player Transformation of Educational Multiplayer Games , 2004 .

[35]  Vincent Aleven,et al.  Toward Tutoring Help Seeking: Applying Cognitive Modeling to Meta-cognitive Skills , 2004, Intelligent Tutoring Systems.

[36]  Ryan Shaun Joazeiro de Baker,et al.  Detecting Student Misuse of Intelligent Tutoring Systems , 2004, Intelligent Tutoring Systems.

[37]  Timothy W. Bickmore,et al.  Towards caring machines , 2004, CHI EA '04.

[38]  Joseph E. Beck,et al.  Engagement tracing: using response times to model student disengagement , 2005, AIED.

[39]  Beverly Park Woolf,et al.  Inferring learning and attitudes from a Bayesian Network of log file data , 2005, AIED.

[40]  Ryan Shaun Joazeiro de Baker,et al.  Do Performance Goals Lead Students to Game the System? , 2005, AIED.

[41]  Kurt VanLehn,et al.  Effects of Dissuading Unnecessary Help Requests While Providing Proactive Help , 2005, AIED.

[42]  Julita Vassileva,et al.  Adaptive Reward Mechanism for Sustainable Online Learning Community , 2005, AIED.

[43]  Ronald H. Stevens,et al.  Machine learning models of problem space navigation: the influence of gender , 2005, Comput. Sci. Inf. Syst..

[44]  John R. Anderson,et al.  Knowledge tracing: Modeling the acquisition of procedural knowledge , 2005, User Modeling and User-Adapted Interaction.

[45]  Vincent Aleven,et al.  Toward Meta-cognitive Tutoring: A Model of Help Seeking with a Cognitive Tutor , 2006, Int. J. Artif. Intell. Educ..

[46]  Ryan Shaun Joazeiro de Baker,et al.  Generalizing Detection of Gaming the System Across a Tutoring Curriculum , 2006, Intelligent Tutoring Systems.

[47]  Beverly Park Woolf,et al.  A Dynamic Mixture Model to Detect Student Motivation and Proficiency , 2006, AAAI.

[48]  Ryan Shaun Joazeiro de Baker,et al.  Adapting to When Students Game an Intelligent Tutoring System , 2006, Intelligent Tutoring Systems.

[49]  Neil T. Heffernan,et al.  Detection and Analysis of Off-Task Gaming Behavior in Intelligent Tutoring Systems , 2006, Intelligent Tutoring Systems.

[50]  Albert T. Corbett,et al.  Designing intelligent tutors that adapt to when students game the system , 2006 .

[51]  Neil T. Heffernan,et al.  Prevention of Off-Task Gaming Behavior in Intelligent Tutoring Systems , 2006, Intelligent Tutoring Systems.

[52]  Antonella De Angeli,et al.  Misuse and abuse of interactive technologies , 2006, CHI Extended Abstracts.

[53]  Lei Qu,et al.  Classifying Learner Engagement through Integration of Multiple Data Sources , 2006, AAAI.

[54]  Neil T. Heffernan,et al.  A Web-based Authoring Tool for Intelligent Tutors: Blending Assessment and Instructional Assistance , 2007, Intelligent Educational Machines.