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Description
The Game As Life - Life As Game (GALLAG) project investigates how people might change their lives if they think of and/or experience their life as a game. The GALLAG system aims to help people reach their personal goals through the use of context-aware computing, and tailored games and applications.

The Game As Life - Life As Game (GALLAG) project investigates how people might change their lives if they think of and/or experience their life as a game. The GALLAG system aims to help people reach their personal goals through the use of context-aware computing, and tailored games and applications. To accomplish this, the GALLAG system uses a combination of sensing technologies, remote audio/video feedback, mobile devices and an application programming interface (API) to empower users to create their own context-aware applications. However, the API requires programming through source code, a task that is too complicated and abstract for many users. This thesis presents GALLAG Strip, a novel approach to programming sensor-based context-aware applications that combines the Programming With Demonstration technique and a mobile device to enable users to experience their applications as they program them. GALLAG Strip lets users create sensor-based context-aware applications in an intuitive and appealing way without the need of computer programming skills; instead, they program their applications by physically demonstrating their envisioned interactions within a space using the same interface that they will later use to interact with the system, that is, using GALLAG-compatible sensors and mobile devices. GALLAG Strip was evaluated through a study with end users in a real world setting, measuring their ability to program simple and complex applications accurately and in a timely manner. The evaluation also comprises a benchmark with expert GALLAG system programmers in creating the same applications. Data and feedback collected from the study show that GALLAG Strip successfully allows users to create sensor-based context-aware applications easily and accurately without the need of prior programming skills currently required by the GALLAG system and enables them to create almost all of their envisioned applications.
ContributorsGarduno Massieu, Luis (Author) / Burleson, Winslow (Thesis advisor) / Hekler, Eric (Committee member) / Gupta, Sandeep (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The gameplay experience can be understood as an interaction between player and game design characteristics. A greater understanding of these characteristics can be gained through empirical means. Subsequently, an enhanced knowledge of these characteristics should enable the creation of games that effectively generate desirable experiences for players. The purpose of

The gameplay experience can be understood as an interaction between player and game design characteristics. A greater understanding of these characteristics can be gained through empirical means. Subsequently, an enhanced knowledge of these characteristics should enable the creation of games that effectively generate desirable experiences for players. The purpose of this study was to investigate the relationships between gameplay enjoyment and the individual characteristics of gaming goal orientations, game usage, and gender. A total of 301 participants were surveyed and the data were analyzed using Structural Equation Modeling (SEM). This led to an expanded Gameplay Enjoyment Model (GEM) with 41 game features, an overarching Enjoyment factor, and 9 specific components, including Challenge, Companionship, Discovery, Fantasy, Fidelity, Identity, Multiplayer, Recognition, and Strategy. Furthermore, the 3x2 educational goal orientation framework was successfully applied to a gaming context. The resulting 3x2 Gaming Goal Orientations (GGO) model consists of 18 statements that describe players' motivations for gaming, which are distributed across the six dimensions of Task-Approach, Task-Avoidance, Self-Approach, Self-Avoidance, Other-Approach, and Other-Avoidance. Lastly, players' individual characteristics were used to predict gameplay enjoyment, which resulted in the formation of the GEM-Individual Characteristics (GEM-IC) model. In GEM-IC, the six GGO dimensions were the strongest predictors. Meanwhile, game usage variables like multiplayer, genre, and platform preference, were minimal to moderate predictors. Although commonly appearing in games research, gender and game time commitment variables failed to predict enjoyment. The results of this study enable important work to be conducted involving game experiences and player characteristics. After several empirical iterations, GEM is considered suitable to employ as a research and design tool. In addition, GGO should be useful to researchers interested in how player motivations relate to gameplay experiences. Moreover, GEM-IC points to several variables that may prove useful in future research. Accordingly, it is posited that researchers will derive more meaningful insights on games and players by investigating detailed, context-specific characteristics as compared to general, demographic ones. Ultimately, it is believed that GEM, GGO, and GEM-IC will be useful tools for researchers and designers who seek to create effective gameplay experiences that meet the needs of players.
ContributorsQuick, John (Author) / Atkinson, Robert (Thesis advisor) / McNamara, Danielle (Committee member) / Nelson, Brian (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Working memory capacity and fluid intelligence are important predictors of performance in educational settings. Thus, understanding the processes underlying the relation between working memory capacity and fluid intelligence is important. Three large scale individual differences experiments were conducted to determine the mechanisms underlying the relation between working memory capacity and

Working memory capacity and fluid intelligence are important predictors of performance in educational settings. Thus, understanding the processes underlying the relation between working memory capacity and fluid intelligence is important. Three large scale individual differences experiments were conducted to determine the mechanisms underlying the relation between working memory capacity and fluid intelligence. Experiments 1 and 2 were designed to assess whether individual differences in strategic behavior contribute to the variance shared between working memory capacity and fluid intelligence. In Experiment 3, competing theories for describing the underlying processes (cognitive vs. strategy) were evaluated in a comprehensive examination of potential underlying mechanisms. These data help inform existing theories about the mechanisms underlying the relation between WMC and gF. However, these data also indicate that the current theoretical model of the shared variance between WMC and gF would need to be revised to account for the data in Experiment 3. Possible sources of misfit are considered in the discussion along with a consideration of the theoretical implications of observing those relations in the Experiment 3 data.
ContributorsWingert, Kimberly Marie (Author) / Brewer, Gene A. (Thesis advisor) / McNamara, Danielle (Thesis advisor) / McClure, Samuel (Committee member) / Redick, Thomas (Committee member) / Arizona State University (Publisher)
Created2018