Instructional Ethology

1. Instructional Ethology Reverse Engineering for Serious Design of Educational Games Katrin Becker, University of Calgary

2. Outline • Studying the Masters • Educational Game Design • Analysis of Commercial Games for Learning • Learning in Games • Successful Games Facilitate Learning • Learning vs. Education • Methodological Synergy • Ontological Excavation • Instructional Ethology • Sample Analysis

3. Studying the Masters

4. Instructional Design Content (what) Receptacle for content Vantage Point: Formal Education Ed. Credentials Educational Game Design Game Design Player Experience (how) Teaching Method Vantage Point: Entertainment (SENG?) Industry Credentials

5. Analysis of Commercial Games for Learning • That players must learn and indeed do learn new things whileplayingthe game; • That successful games are successful at least partially because theyfacilitate that learning; and • That it is possible to examine learning in a digital game without associating what is learned with value-laden educational aims. Three fundamental assumptions:

6. Learning in Games • Already Happening • Learning is what we DO • Learning is how we win the game.

7. Successful Games Facilitate Learning

8. Learning Value-Neutral Can be Coincidental Natural Internally Motivated* Learning vs. Education Education Value-Laden Deliberate Coerced/Persuaded Externally Motivated*

9. Methodological Synergy Behavioural Analysis Structural Analysis Analysis Ethology Ontological Excavation Game as Object Game Ethology (dynamic) Game Structure (static)

10. Black Box Reverse Engineering Byrne, E. J. (1992). A Conceptual Foundation for Software Re-engineering. Proceedings of the International Conference on Software Maintenance, Orlando, FL, USA, 9-12 Nov 1992, p. 326-335.

11. Ontological Excavation

12. Ontological Excavation of Games

13. Ethology

14. Ethology • Causation. What are the stimuli that elicit the response, and how has it been modified by recent learning? • Function: How does the behaviour impact on the animal's chances of survival and reproduction? • Development: How does the behaviour change with age, and what early experiences are necessary for the behaviour to be shown? • Evolution: How does the behaviour compare with similar behaviour in related species, and how might it have arisen through the process of phylogeny?

15. Instructional Ethology

17. Analysis – Ultimate Goal: to match behaviours with objectives

18. Sample Analysis

19. Analysis: Morphology • High conceptual coherence • ‘scores’, game space, set-up, levels • ‘Standard’ controls Note: this process is time consuming – goal is to build more detailed queries about behaviour based on the initial observations.

20. Analysis: Ethology, Causation (Interaction) • Use rod • Catch fish • Timing • ‘Line of sight’ • Position of avatar • Residents talk about fishing • Some are easy to catch; others hard • Some are common; others rare Not especially interesting at first glance, but behaviour BECOMES interesting when Reviewed in light of other aspects.

21. Analysis: Ethology, Development (Ontogeny, Game Flow) • Very little change in the game over the life of the game  the change is almost all in the player • Effect is predictability • Few penalties beyond immediate one.

22. Analysis: Ethology, Evolution • Previous animal crossing (with adaptations for platform) • Limited RPG style / sim ancestors • Format: • Changes in choices (options include only those that make sense) • Pockets • Currency

23. Analysis: Ethology, Function (purpose) – how does it help players? • Size of fish; Location, season, time of day, shape, sound (frog) • Contests • Collections • game keeps track for you • Provides 2 ways to collect • Bells for fish • Experience..... • Minimal penalties for misses • Effort is rewarded • can always sell what you catch, even if it’s not what you wanted

26. Next Steps • Compare good & bad games • Compare Commercial & Educational Games • More perspectives • More games • Streamline process

27. Thanks!