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
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
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.
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
