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Gaming the System in the CALL Classroom

Gaming the System in the CALL Classroom. Peter Gobel Kyoto Sangyo University pgobel@cc.kyoto-su.ac.jp. Introduction. J. Carrol (1963)- time on task hypothesis: the learner will succeed in learning a given task to the extent that he spends the amount of time that he needs to learn the task.

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Gaming the System in the CALL Classroom

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  1. Gaming the System in the CALL Classroom Peter Gobel Kyoto Sangyo University pgobel@cc.kyoto-su.ac.jp

  2. Introduction • J. Carrol (1963)- time on task hypothesis: the learner will succeed in learning a given task to the extent that he spends the amount of time that he needs to learn the task. • Baker et. al (2004a)- off-task behavior associated with reduced learning

  3. Cont. • Baker et. al (2004b)- gaming the system (misuse of tutoring systems) associated with substantially lower learning. 1/3 less than those who do not engage in this behavior. • Learned helplessness and ‘performance orientation’ related to gaming.

  4. Basic Question • Is motivation related to misuse of the system or inappropriate help-seeking?

  5. Research Questions In Japanese university students: • Is frequency of off-task behavior a predictor of test performance? • Does the kind of off-task behavior make a difference? • Are motivational factors predictors of performance behavior and test performance?

  6. Kyoto Sangyo CALL Curriculum • Students • lower proficiency non-English majors • System • meeting 90 minutes/week • DynEd • ALC • Course requirements • grade linked to completion of level tests and time spent on software system

  7. Participants • Three intact classes - 105 students • All non-English majors • All streamed at low level

  8. Observation • Off-task behavior (physical and virtual) • Non-system related activity • Inactivity • Misuse of system (gaming) • On-task behavior (physical and virtual) • Appropriate system-related activity • Seeking help from peers, software, and teacher

  9. Observation (continued) • Total amount of study time • Recorded automatically by software system • Study score • Based on total amount of study time and ‘proper’ use of the software.

  10. Observation (continued) Test performance • Gain scores on general proficiency test • Listening section • Reading section • Administered in April and July

  11. Motivation Questionnaire • 35seven-point Likert scale items • administered in Japanese • 30 items were written referring mainly to motivational theory • 5 items referring to CALL activity

  12. Questionnaire Items • Expectancy for success • Attainment Value • Intrinsic value • Extrinsic utility value • Cost • Attitudes toward target group • Effort • CALL related items

  13. Observation Off-task behavior On-task behavior Total study time Study score Questionnaire Structure Motivational predictors of performance Motivational predictors of behavior Results

  14. Classroom Observation

  15. Off-task behavior • Off-task non software • Off-task inactive • Off-task software • Help • Study record • Off-task gaming

  16. On-task behavior • On-task software • Microphones and speech analyzers seldom used • Certain activities overused and recycled • On-task help • Rarely used • Translation rarely used

  17. Behavior Regression Results • Whether students were generally off task or on task was a significant predictor of test performance. • Gaming was not a significant predictor of test performance.

  18. Listening Gain Study Score a significant predictor of performance Reading Gain Study Score &Total Study Time significant predictors of performance. Behavior Regression Results

  19. Questionnaire resultsFour factors • Attitudes toward the target group • Perceived usefulness of studying English • Expectancy for success • Attitude towards CALL

  20. Motivation regression analysis • Factor 1 (Attitudes towards the target group) was a predictor of gain scores in both listening and reading, but not for behavior.

  21. Research Questions Revisited • Task behavior was a predictor of test performance. • The kind of off-task behavior did not make a difference. • Attitude toward the TG was a predictor of test performance, but not off/on-task behavior.

  22. Conclusion • Off-task behavior • Evidence of off-task behavior related mostly to inactivity rather than gaming • On-task behavior • All aspects of the software not fully used • Motivation • Attitude towards TG most important for effective CALL use

  23. References • Baker, R. S., Corbett, A. T., Koedinger, K. R., & Wagner, A. Z. (2004). Off-task behavior in the cognitive tutor classroom: When students ‘game the system’. Proceedings of ACM CHI 2004: Computer Human Interaction, 383-390. • Baker, R. S., Corbett, A. T., & Koedinger, K. R. (2004). Detecting student misuse of intelligent tutoring systems. Proceedings of the Seventh International Conference on Intelligent Tutoring Systems, 531-540. • Carrol, J. (1963). A model of school learning. Teachers College Record, 64(8), 723-733.

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