This document summarizes research analyzing gameplay data from a simulation game designed to teach diffusion of innovations theory. The researchers assessed which strategies were most successful in the game by comparing patterns of frequent activities, sequences, and joint occurrences between groups that successfully or unsuccessfully adopted all innovations. While some predicted strategies from diffusion theory were more common in successful games, others were not. The researchers suggest future work to collect more granular data and address misconceptions through instructional strategies like debriefing.

1. Assessment of Strategies in the Diffusion Simulation Game Jake Enfield jwenfiel@indiana.edu Rod Myers rodmyers@indiana.edu Instructional Systems Technology Indiana University - Bloomington

2. Research Goal Analyze gameplay data to assess the fidelity of the game with the theory it is designed to teach. 2

3. Key Concepts Diffusion of Innovations Theory DSG - Simulation game for learning Fidelity of simulations Analysis of Patterns in Time (APT) 3

4. Diffusion of Innovations Theory Everett Rogers Source: http://www.12manage.com/methods_rogers_innovation_adoption_curve.html 4

5. Demo of DSG new version (beta) 5

6. 6 Current Version ~ Detailed View

7. Predicted Successful Strategies Get to know the staff Take a client-oriented approach Utilize opinion leaders Provide opportunities for staff to evaluate the innovation Select mass media communication channels to raise awareness of the staff early in the game. Utilize interpersonal channels Utilize early adopters 7

9. 2361 Completed Games

10. 341 Successful Games (all 22 adopters)

12. Findings & Discussion Research Question 1:What strategies were successful in the game sessions being studied? Most frequently used activities Most frequent sequences of activities Most frequent joint occurrences (activity + targeted faculty) 10

14. Pilot Test (5 : 1)

15. Talk To  Talk To

16. Talk To  Ask Help

17. Talk To  Talk To  Talk To  Talk To

19. Site Visit (3 : 1)

20. Local Mass Media (2 : 1)

21. Talk To  Talk To

22. Print  Print

23. Print  Print  Print  Print

24. Opinion Leaders: Demonstration (1.5 : 1)11

25. Findings & Discussion Research Question 2: Are the strategies that were successful within the game aligned with strategies that would be predicted by the diffusion of innovation theory? Only 3 of the 7 predicted strategies were employed more frequently in successful games. 12

26. Findings & Discussion <<< APPARENTLY >>> Get to know the staff Take a client-oriented approach Utilize opinion leaders Provide opportunities for staff to evaluate the innovation Select mass media communication channels to raise awareness of the staff early in the game. Utilize interpersonal channels Utilize early adopters 13

28. Sequences

29. Joint Occurrences14

30. Limitations Extant Data (Adoption Stage, player id) Relative frequencies as metric 15

31. Future Research Follow up study with additional data collected Designing a data collection method to support APT (data collected at a granular level) and developing a pattern query tool Use of instructional strategies to support learning and address misconceptions (such as debriefing) 16

32. References DIFFUSION SIMULATION GAME. (1976). Molenda, M., & Young, P. Bloomington, IN: Indiana University, 201 North Rose Avenue, Bloomington, IN 47405-1006. Frick, T. W. (1990). Analysis of patterns in time (APT): A method of recording and quantifying temporal relations in education. American Educational Research Journal, 27(1), 180-204. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: The Free Press. 17

33. You can play too! Production version v.1: http://www.indiana.edu/~istdemo New version (beta): http://www.indiana.edu/~simgame/dev/dsg.html 18