implementing a SDT based motivation model in a serious game

1. Career Quest
Behind the Curtain

2. De-Brief
• Purpose of game
• Learning goals and implementation
• Experiment design and implementation

3. Affect & SGs
• e-Bug == Cognitive focus + Affective instinct
• i.e. “I’ll design it to be fun”
• The fun of those games is derived from stealing
things from games.
• Platform mechanics
• Story / comedy
• scores etc

4. Affect and e-Bug
• Why is the e-Bug game “fun” for 9-11 year olds?
• Why is ANY game fun?
• Why is anyTHING fun?

5. SPAM / ARC
• DM spoke of the (S)PAM model of motivation
(Daniel Pink).
• Does anyone remember what it is?
• DM spoke of the ARC model of motivation (Deci &
Ryan).
• Does anyone remember what it is?

6. Intrinsic Motivation
• Autonomy (a feeling of having freedom, that your
choices matter and you can express change)
• Relatedness (a feeling of connection to people, that
you & what your doing matters to your peers)
• Competence (a feeling that you are good at
something or are getting better at something)

7. Support for ARC
• How much people feel supported in Autonomy,
Relatedness and Competence predicts their
subjective enjoyment of a task and the extent to
which they identify with the task.
• People who identify as intrinsically motivated
perform better and learn / remember more.

8. ARC & Learning
• Grolnick & Ryan 1987
• 3 groups of children at school
• nondirected (asked to read a passage and
report how interesting.)
• directed (no mention of test but told instructor
interested in how much they learn)
• directed and told about grades

9. ARC & Learning
• The first two of these groups attempt to give
autonomy (not DIRECTING behaviour)
• All students tested.
• Students who were directed performed better on
rote memorisation than first group.
• grades group (least autonomous) evidenced
greatest deterioration of memorised facts after a
week)
• grades group also had poorer conceptual
learning of material than other groups.

10. ARC & Learning
• Similar findings repeatedly found.
• Generalisable finding is that when people are “self
determined” in a learning task, they are more
engaged, pay more attention, want to learn more
and retain / understand better as a result.
• Sounds like an important finding to me!

11. Games
• Is SPAM / ARC why we like games?
• Some think so. I’m starting to (ish).
• Lots of (fake) Autonomy.
• Relatedness is weaker (multiplayer excepted)
• “balance” + great, timely feedback ==
Competence

12. ARC in Games
• Rigby & Przybylski 2006 found:
• that satisfying ARC related to:
• intrinsic motivation for play
• immersion in the game
• +ve short term wellbeing in the player
• mastery of controls essential but not sufficient

13. ARC in Games
• Rigby & Ryan 2006 found:
• “between-games differences in psychological
need satisfaction related to popular appeal”
• Two games very similar in content but judged
differently by metacritic.
• The ‘good’ game supported ARC better than the
‘bad’ game.

14. ARC & Games
• Przybylski, Ryan and Rigby 2009 found:
• Core appeal of violent games was based on
ARC satisfaction
• ARC predicted enjoyment, immersion and future
play. Violent interests / tendencies predicted
preference for future play - but NOT enjoyment.
• Przybylski 2009 found that post-play aggression
was not linked to violent content, but rather to low
ARC support - e.g. frustration from poor mastery

15. Hypotheses
• Enjoyment of a Serious Game is predicted by
perceived ARC support
• As self reported by players
• As objectively measured
• Knowledge & Attitude change will be correlated to
ARC support
• Certain game design strategies will support ARC
better than others

16. Careers Service
• Students don’t really think about employability until
after graduation.
• Students think “get my degree then worry about it”
• Students think they have no skills outwith their
degree and that their P/T work doesn’t matter
• Asked if we could design a game to try to tackle
these.

17. Learning Design
• The “Fortnightly Planner” is to raise awareness of
what is required to manage one’s employability.
• The “Dilemmas” were to make students think about
employability skills outside of their degree.
• The “Daily Item” was intended to encourage not just
“playing the game” but taking the content of the
game into your real world.

18. Hypotheses
• Enjoyment of a Serious Game is predicted by
perceived ARC support
• As self reported by players
• As objectively measured
• Knowledge & Attitude change will be correlated to
ARC support
• Certain game design strategies will support ARC
better than others

19. Experiment Design
• We want see if ARC support correlates to
subjective engagement, objective engagement, and
K&A change.
• The different “versions” of the game are intended to
answer the third hypothesis.

20. Autonomy Support
• High:
• Empowering Language
• More agency by type / quantity
• Medium:
• Neutral language
• Medium agency by type / quantity
• Low:
• Controlling language
• Low agency by type / quantity

21. Competence
• Vary
• Detail of feedback
• Language that suggests improvement / is
neutral / or suggests poor performance
• Information in advance for how their choices will
affect their attainment varying to no information

22. Relatedness
• High group received detailed, personal feedback at
the start of each week.
• Low group had an avatar we hoped they wouldn’t
relate to (if also in low Autonomy group)

23. Demo

24. Early findings
• K&A wise, I know of some changes to behaviour
via the “daily task”
• 12 students signed up for vacancies (1 got a
game design job ?!?!?!?!)
• At least one student did the “twitter” daily task.
• 6 students got the token from CS - they now know
where it is!

25. Early Findings
• Of the NINE “High A, High C” students, only ONE
chose to answer their own solution to dilemmas.
• struck me as a bit weird!
• People did not behave as I would have predicted
SOLELY by their (random) groups
• one of the most frequent users was a “low
everything” user.

26. Results
• Of course, for all but last of the hypotheses it’s
“perceived” ARC support that matters.
• One objective measure of engagement was daily
option submissions.

27. Daily Engagement
• Excluding the HACKER who had 77....
• Very crudely, adding AC support values (0,1,2) and
calling it SDT:
4 = 23 / 7 = 3.3
3 = 7 / 4 = 1.7
2 = 18 / 12 = 1.5
1 = 12 / 4 = 3
0 = 33 / 10 = 3.3
• I can see no sign of design’s influence
• I suspect personality had larger impact than my
design

28. This afternoon
• Focus group questions
• Please think about the game.
• Think about whether you felt supported in ARC
• Whether the game mechanics influenced this
• What you liked /disliked, what you would change
etc.