Presentation at the 4th International Computer Game Conference Cologne May 23-25, 2012. Questions and feedback are more than welcome!

1. A multidimensional approach for
studying ‘engagement’ and learning
in instructional games.
Michael Filsecker, Duisburg-Essen University
michael.filsecker@uni-due.de

2. Introduction
Arguments
Inconclusive
Are games effective
for learning? (Dempsey et al., 1996)
Are games effective
for motivating to learn?
Research practices
(1) “proof of concepts”,
(2) undeveloped “theory of action”,
(3) lack of control groups, Limited research
(4) games +other learning activities base
(5) lack of common definitions and
(NRC, 2011)
terminology
Understand „learning from educational games“
Inform practice (use and design) 2

3. Our „Black box“?
Input Process Output
• Prior knowledge • Cognitive
• VG Self-efficacy • Memorize
• Interest information
• Gender • Understanding
• Motivation relatioships
• Preconceptions • Apply skills
• Usability Kolb‘s cycle:
• Apply generic
Assimilation- skills
• G literacy accomodation CO-RO-AC-AE
Flow: „Game cycle“:
A-S-C J-B-F
• Game • Motivational &
characteristics Affective
• Content • Interest
knowledge • Intr. Motivation
3

4. Procedural
Engagement
Conceptual Gresalfi et al. (2009)
Consequential Engaged participation Hickey (1997)
Engaged learning Jones et al. (1992)
Productive
Engel & Conant (2002)
Disciplinary
Motivated Habgood (2005) Mindfulness Salomon (1984)
Cognitive Intentional learning Bereiter & Scardamalia (1989)
Behavioral Fredriks et al. (2004) Committed learning diSessa (2000)
Emotional
4

5. Quest Atlantis &
Assessment

6. Motivation-Volition
Approach/avoidan
Goal setting
ce tendencies
Conception of Action-control:
Desicion
learning making • Resource
(goal) allocation
Perception of the
task Goal related
Action-goal
Commitment
cognition:
• Mindful effort
• Strategie use
Implementation (goal
execution)
Consequences:
• Flow + affects
Goal engagement • Learning
Corno (1993) 6

7. Engagement
Multidimentional construct involving different cognitions,
behaviors and emotions that reflect volitive aspects
of the motivational process
Cognitive = investment in learning and includes self-regulation, thoughtfulness,
and willingness to go beyond the basic requirements to master difficult skills .
Behavioral = active participation and includes effort, concentration, attendance,
following the rules, and avoiding trouble.
Emotional = the extent a person experiences positive and negative reactions to
teachers, peers, and activities in general, and includes emotions such as interest,
enjoyment, enthusiasm, feelings of belonging and valuing of learning.
Fredericks et al (2004); Bohnert et al. (2010) 7

8. Tendencies…
Tendencies that
Provide a richer
Understanding of…
…how people
Interact with technology
Time scale
Questionnaires
8

9. Our „Black box“?
Input Process Output
• Prior knowledge • Cognitive
• VG Self-efficacy • Memorize
• Interest information
• Gender • Understanding
• Motivation relatioships
• Preconceptions • Apply skills
ycle: • Apply generic
• Usability
• G literacy
Behavioral Cognitive
CO-RO- skills
AC-AE
„Game
Flow:
“:
A-S-CEmotional
• Game
J-B-F • Motivational &
characteristics Affective
• Content • Interest
knowledge • Intr. Motivation
9

10. Conceptual Framework
Amount of invested effort (Salomon, 1984)
Mental effort (Paas et al., 1992) Questionnaires
Cognitive Depth of processing (Clairk & Lokhart, 1972)
Cognitive engagement (Corno & Mandinach, 1983) Interview
Attention allocation and cognitive processes
(Just & Carpenter, 1980) Eye movements
Behavioral
Visual attention (Duchowski, 2007)
Intrinsic motivation – Flow-
Enjoyment (Rheinberg & Vollmeyer, 2003) Questionnaires
Emotional
Interest
10

11. The Pilot Study

12. The Game Unternehmen Physikus
Simulation &
Edutaiment
Game elements
Tasks/Exercises: Role of
Physics enterpreneur
Goal: Develop
your own
company
12

13. The experimental session
Questionnaire
Survey Gameplay Interview Recall test
(CE)
Preconceptions Play Learn t
Self-efficacy 17 20 -1,567
Easyness 10,67 11 -0,233
Usefulness 5,17 7,17 -1,395
Game experience 2,17 4 -2,607*
Cog. Engagement 13,33 13,50 -0,146
13

14. Results
20 yr. Old undergraduates (n=16). 20 min playtime
Two conditions (pre-post):
- Instructed to learn („learn as much as you can while playing” )
- Instructed to play for fun („have fun while playing the game”)
Dependent variables:
[AIME (Salomon, 1984) and Mental effort (Pass, 1992) (ME)]=CE
(Fredriksen et al., 2004), eye movements;
Control variables: game exp & Self-effic., perception of games.
Sig. difference on Mental Effort & recall
No sig. difference on AIME
No sig. Correlation between K. page & Learning & ME
But, different corr. Pattern K. page & Learning & ME.

15. Examples of information processing
during gameplay
Condition to learn Condition for fun
15

16. Study 2
Undergraduates (n=42). 30 min playtime
Two conditions (pre-post):
- Instructed to learn
(„learn as much as you can about physics while playing “)
- Instructed to play for fun
(„have fun while playing the game”)
Dependent variables: AIME, Situational cognitive
Engagement, AIME & Mental effort (ME), learning
Eye movements + Interview
Control variables: game experience & Self-efficacy
No sig. diff. Between conditions 16

17. Example of scanpath
N=15
15,38% of the individuals
engaged in a pairwise
comparison between AOIs
(only 2 AOIs hit),
70% of them used more
“overview” scanning (three,
four and five AOI hits).
(See Holmqvist et al., 2011)
17

18. The next question
• Cognitive engagement or flow moderates the
relatioship between motivation and learning
while playing educational games?
Cog. Eng.
a b
Motivation Learning
c
a' b'
Flow
18
18

19. Thank you!
Michael Filsecker, Duisburg-Essen University
Michael.filsecker@gmail.com
Michael.filsecker@uni-due.de