G4LI Games for Learning Day at G4C 2011

1. Covert and overt measures of engagement within an educational multimedia environment. This research was supported by Office of Naval Research underGrant N00014-10-1-0143 awarded to Dr. Robert Atkinson Robert M. Christopherson,Javier Gonzalez-Sanchez, Mustafa Baydogan,Maria Elena Chavez-Echeagaray, David-GibsonRobert Atkinson lsrl.lab.asu.edu

2. Games can change the way we learn Empirical research can change the way we game

3. Learning Gaming surprise happiness flow/engagement anger delight boredom frustration confusion curiosity anxiety fear

4. Goals Education: Engagement = Learning Games: Engagement = Fun

5. Overt - observable Covert - hidden

6. Overt and Covert Facial expressions Cognition Verbalization Motivation Behavior Flow Engagement Attitude Performance Emotion Physical interactions Posture

7. What is engagement? Gaming “concerned with all the qualities of an experience that really pull people in – whether this is a sense of immersion that one feels when reading a good book, or a challenge one feels when playing a good game, or the fascinating unfolding of a radio drama” Benyon and colleagues (2005)

8. What is engagement? Learning “the nexus of intrinsic knowledge and interest and external stimuli that promote the initial interest in, and use of a computer-based learning environment” (Jones, 1998)

9. Measuring Engagement Objective Observational Analysis Physiological data Cognitivewalkthrough Think-aloud HeuristicEvaluation Qualitative Quantitative Interviews &Focus Groups Surveys & Questionnaires Subjective

10. Use of Physiological Data Decide what you want to measure Choose the appropriate sensors Control your task and environment Process the data according to which sensors were chosen Make inferences, evaluate and revise

11. 1. Decide what you want to measure engagement arousal mental effort attention excitement boredom meditation frustration

12. 2. Choose the appropriate sensors

13. 3. Control your task and environment Con 20 Users playGuitar HeroTM easy and hard song 15 mins of practice Skin/Eye/Head/Guitar sensors

14. Real Time Monitoring

15. 4. Process the data according towhich sensors were chosen

16. 5. Make inferences and iterate on game/instructional design Visualization Interpretation Datamining Statistics

17. High Scoring Performance in Guitar HeroTM ––––– Raw Engagement ––––– Median Engagement ––––– Normalized Performance

18. Low Scoring Performance in Guitar HeroTM ––––– Raw Engagement ––––– Median Engagement ––––– Normalized Performance

19. Engagement

20. Boredom

21. Meditation

22. Frustration

23. Long Term Excitement

24. Why measure engagement? Dynamic Difficulty Adjustment Expand Demographics Longer Time on Task

25. Dynamic Difficulty Adjustment Challenge Anxiety Flow Zone Boredom Ability

26. Expand Demographics Challenge Expert Flow Zone Novice Ability

27. Time on Task FLOW TIME

28. ROI in Games Competitive edge Broader appeal Micro and macro evaluation Personalization Improve gameplay

29. ROI in Education Increase Performance Retention Time on task Attitude toward learning

30. Ongoing Work SeductiveDetails (Instructional Design) Videogames and Engagement (Guitar Hero) Emotions and Working Memory Capacity (puzzles) 3D Instructional training (US Navy, Save Science) Affective Meta Tutor

31. Questions? lsrl.lab.asu.edu