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Mfilsecker engagement and educational games
 

Mfilsecker engagement and educational games

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Presentation at the 4th International Computer Game Conference Cologne May 23-25, 2012.

Presentation at the 4th International Computer Game Conference Cologne May 23-25, 2012.

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    Mfilsecker engagement and educational games Mfilsecker engagement and educational games Presentation Transcript

    • A multidimensional approach forstudying ‘engagement’ and learning in instructional games. Michael Filsecker, Duisburg-Essen University michael.filsecker@uni-due.de
    • IntroductionArguments 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
    • 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
    • Procedural Engagement Conceptual Gresalfi et al. (2009)Consequential Engaged participation Hickey (1997) Engaged learning Jones et al. (1992)Productive Engel & Conant (2002)DisciplinaryMotivated Habgood (2005) Mindfulness Salomon (1984)Cognitive Intentional learning Bereiter & Scardamalia (1989)Behavioral Fredriks et al. (2004) Committed learning diSessa (2000)Emotional 4
    • Quest Atlantis & Assessment
    • Motivation-VolitionApproach/avoidan Goal setting ce tendencies Conception of Action-control: Desicion learning making • Resource (goal) allocationPerception 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
    • EngagementMultidimentional construct involving different cognitions, behaviors and emotions that reflect volitive aspects of the motivational processCognitive = 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 toteachers, 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
    • Tendencies… Tendencies that Provide a richer Understanding of… …how people Interact with technology Time scaleQuestionnaires 8
    • 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
    • Conceptual Framework Amount of invested effort (Salomon, 1984) Mental effort (Paas et al., 1992) QuestionnairesCognitive Depth of processing (Clairk & Lokhart, 1972) Cognitive engagement (Corno & Mandinach, 1983) Interview Attention allocation and cognitive processes (Just & Carpenter, 1980) Eye movementsBehavioral Visual attention (Duchowski, 2007) Intrinsic motivation – Flow- Enjoyment (Rheinberg & Vollmeyer, 2003) QuestionnairesEmotional Interest 10
    • The Pilot Study
    • The Game Unternehmen Physikus Simulation & Edutaiment Game elements Tasks/Exercises: Role of Physics enterpreneur Goal: Develop your own company 12
    • The experimental session QuestionnaireSurvey 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
    • Results20 yr. Old undergraduates (n=16). 20 min playtimeTwo 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 & recallNo sig. difference on AIMENo sig. Correlation between K. page & Learning & MEBut, different corr. Pattern K. page & Learning & ME.
    • Examples of information processing during gameplayCondition to learn Condition for fun 15
    • Study 2Undergraduates (n=42). 30 min playtimeTwo 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 cognitiveEngagement, AIME & Mental effort (ME), learningEye movements + InterviewControl variables: game experience & Self-efficacy No sig. diff. Between conditions 16
    • 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
    • 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
    • Thank you!Michael Filsecker, Duisburg-Essen University Michael.filsecker@gmail.com Michael.filsecker@uni-due.de