Foundation for Measuring Engagement in Educational Games
Kristian Kiili
Timo Lainema
As of yet, research has not been done that informs the effective design of educational games for learning. The authors stress that we need to develop theoretical foundation for game-based learning.
Kiili(2005) did an experiment to help designers find what makes a game enjoyable. The study incorporates the principles of engagement from Csikzzentmihalyi (1991): “Flow describes a state of complete absorption or engagement in an activity and refers to the optimal experience” (470). Malone(1980) identified four main ways which games motivate people: fantasy, challenge, curiosity, and control.
Experiential gaming:
The expiential gaming model describes the learning process through games, supports the development of engaging educational games, describes the game design process. This model shows “flow” stemming from challenges, gamefulness, playability, and solution generation. Flow itself generates schemata construction, positive attitudes, and active experimentation (472).
Operationalization of Flow in Educational Game Context:
There is still work to be done in operationalizing flow before valid empirical research can be conducted. Operationalization of flow here is based on the elements of experiential gaming and can be divided into three groups:
Flow antecedents – Clear goals, immediate feedback, gamefulness, frame story, and playability. These are factors that contribute to the flow state. The authors make a distinction between learning and controlling the game, saying controlling is spontaneous and automatic, while educational content should be processed and reflected on. The frame story of the game integrates the challenges (and the educational content) into a certain context. Games should have situated, practical challenges. Gamefulness is about the level of freedom a player has in the game.
Flow state – In flow a person is focused and forgets unpleasant things. Flow requires complete concentration, thus self disappears from awareness. Time does not pass as it normally would, and the experience is autotelic, the reward being playing the game itself. A sense of player control also contributes to the flow state.
Flow consequences – Flow enhances learning (a number of authors on 475). Problem-based gaming (founded on principles of problem-based learning) emphasizes authentic learning tasks, experiential learning, and collaboration. Players also test different kinds of solutions (exploratory behavior).
Methods:
This study focused on the hypotheses that all flow antecedents would have positive effects on the flow experience, and that flow experience has a positive impact on learning and exploratory behavior.
This study was done using a business simulation game intended to enhance students’ decision making skills. The study was administered to 92 students in a school of economics. Students worked in a team to save a failing company.
Data was gathered with a GameFlow questionnaire beforehand using 5-point Likert-type responses. Then the game was played twice with each student group, introductory sessions and then actual gaming sessions. Two weeks later, groups returned to play under a more complex environment.
Results:
The students’ general response was that they liked the game and would play again the future. The questionnaire did not provide reliable results.
Results indicated that there was a loose positive correlation between flow state and learning. However, learning was not directly measured. Only students feelings about learning were measured.
Conclusion: flow antecedents should be considered during game design.
Also, flow experience differs from immersion in that in flow experience a player is totally focused on a goal, while immersion means the player becomes part of the activity itself. Flow has voluntary direction of attention, and is more interesting for educational games than immersion.
Kiili, K., &; Lainema, T. (2008). Foundation for Measuring Engagement in Educational Games. J of Interactive Learning Research, 19(3), 469–488.
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Interactivity in Multimedia Learning: An Integrated Model
Steffi Domagk, Ruth N. Schwartz, Jan L. Plass
Interactivity involves the notion that students have to become actively engaged for deeper learning to occur. Yet studies of interactive environments have found both advantages and disadvantages. This may depend on different definitions of interactivity – be it whether the learner can control the pace of the presentation or control the user response and system feedback. It may also be defined as organizing instructional content or as a computer as a “social actor.” Most definitions of interactivity agree that is requires two conditions, atleast two participants must interact and the actions of these participants must include an “element of reciprocity”- change occurs on both sides. Thus, the authors have created an updated definition of interactivity: “Interactivity in the context of multimedia learning is reciprocal activity between a learner and a multimedia learning system, in which the (re)action of the learner is depended upon the (re)action of the system and vice versa” (2).
INTERACT is the Integrated Model of Multimedia Interactivity. It combines the environment’s and learner’s variables in a loop comprising behavioral activity, the learning environment (system design and affordances), (meta)cognitive activity, emotion/motivation and the mental model (3).
Three design features are frequently associated with interactivity. Learner control can mean control over pacing, control over content or control over representation; this directly targets behavioral activity. Guidance and feedback, in an INTERACT standpoint, aim to promote learner’s (meta)cognitive activities. Therefore it usually indirectly targets behavioral activity. However, guidance can be a noninteractive feature (asking learners to reflect after an activity).
Domagk, S., Schwartz, R., & Plass, J.L. (in press). Interactivity in Multimedia Learning: An integrated Model. Computers in Human Behavior.
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Article of choice:
Video games: What they can teach us about audience engagement
James Paul Gee
Gee, J. (2010). Video games: What they can teach us about audience engagement. Nieman Reports, 64(2), 52.
Video games are not driven by content, but instead by player choices. When we play, we expect to learn new things. In content-driven media, we learn by being told and then reflecting on the new information, but there is no guarantee that we will reflect. With games, we have to reflect because our choices effect whether we win or lose. We learn in games from designed, guided experiences. Games have a low cost for failure, meaning, players fail a lot, but they can restart easily, so they take risks. Games allow players to master skills by learning by doing- players are learning from their own experiences, not someone else’s. Players learn about solving problems with constraints. Players are active, and absorb information by doing, not reading.
Katya's Educational Technology Experience 