Games -- Psychological aspects, Learning, Play -- Psychological aspects
In this dissertation, the relationship between flow state, serious games, and learning was examined. Serious games, which are games that convey something other than enjoyment (e.g., learning), are increasingly popular platforms for research, training, and advertisement. The elements that make serious games useful to researchers, trainers, and practitioners are closely linked to those that make up the positive psychology construct of flow state. Flow state describes an optimum experience that is encountered when a variety of factors are met, and is characterized by high focus, engagement, motivation, and immersion. While flow state is often discussed in the serious games literature, in-depth empirical examinations of flow state remain elusive. In this dissertation I addressed this need by conducting a thorough literature review of flow, serious games, and game-based learning in order to propose a new model of flow in games. Two studies were conducted in support of this model. The first experiment consisted of the creation and validation of a play experience scale. Based on the data from 203 Study 1 participants, the Play Experience Scale was validated for use with video games. The 14-item version of the Play Experience Scale was composed of the components of freedom, lack of extrinsic motivation, autotelic experience, and direct assessment of play. The scale was reliable, with a calculated α of .86. In the second study, the newly developed scale was used alongside an immune system serious game to examine the impact of play, in-game performance, and emotional experience on flow in games. In an effort to provide a more symmetrical version of the scale, two items were added to the scale, iii resulting in a 16-item revision. Based on the empirical results obtained from Study 2’s 77 participants, the proposed model of flow in games was revised slightly. Though Study 2 only examined a subset of the overall model of flow in games, the evidence suggested the model was a good theoretical match. Further, the two added items of the Play Experience Scale were valid, providing a final 16-item version of the scale. Play and in-game performance were key predictors of game-based learning. Additionally, play, video game self-efficacy, and emotional experience exhibited a reciprocal relationship with flow state. Implications for serious game development, scientific research into games and learning, and industry testing of game playability were provided. Following these implications, conclusions were presented alongside suggestions for further research.
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Doctor of Philosophy (Ph.D.)
College of Sciences
Applied Experimental and Human Factors
Length of Campus-only Access
Doctoral Dissertation (Open Access)
Dissertations, Academic -- Sciences, Sciences -- Dissertations, Academic
Pavlas, Davin, "A Model Of Flow And Play In Game-based Learning The Impact Of Game Characteristics, Player Traits, And Player States" (2010). Electronic Theses and Dissertations. 1657.