4 resultados para Video Games

em Research Open Access Repository of the University of East London.


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Conventional taught learning practices often experience difficulties in keeping students motivated and engaged. Video games, however, are very successful at sustaining high levels of motivation and engagement through a set of tasks for hours without apparent loss of focus. In addition, gamers solve complex problems within a gaming environment without feeling fatigue or frustration, as they would typically do with a comparable learning task. Based on this notion, the academic community is keen on exploring methods that can deliver deep learner engagement and has shown increased interest in adopting gamification – the integration of gaming elements, mechanics, and frameworks into non-game situations and scenarios – as a means to increase student engagement and improve information retention. Its effectiveness when applied to education has been debatable though, as attempts have generally been restricted to one-dimensional approaches such as transposing a trivial reward system onto existing teaching materials and/or assessments. Nevertheless, a gamified, multi-dimensional, problem-based learning approach can yield improved results even when applied to a very complex and traditionally dry task like the teaching of computer programming, as shown in this paper. The presented quasi-experimental study used a combination of instructor feedback, real time sequence of scored quizzes, and live coding to deliver a fully interactive learning experience. More specifically, the “Kahoot!” Classroom Response System (CRS), the classroom version of the TV game show “Who Wants To Be A Millionaire?”, and Codecademy’s interactive platform formed the basis for a learning model which was applied to an entry-level Python programming course. Students were thus allowed to experience multiple interlocking methods similar to those commonly found in a top quality game experience. To assess gamification’s impact on learning, empirical data from the gamified group were compared to those from a control group who was taught through a traditional learning approach, similar to the one which had been used during previous cohorts. Despite this being a relatively small-scale study, the results and findings for a number of key metrics, including attendance, downloading of course material, and final grades, were encouraging and proved that the gamified approach was motivating and enriching for both students and instructors.

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REVERIE (REal and Virtual Engagement in Realistic Immersive Environments) [1] is a multimedia and multimodal framework, which supports the creation of immersive games. The framework supports the creation of games integrating technologies such as 3D spatial audio, detection of the player’s body movement using Kinect and WIMO sensors, NPCs (Non-Playable Characters) with advanced AI capabilities featuring various levels of representation and gameplay into an immersive 3D environment. A demonstration game was developed for REVERIE, which is an adapted version of the popular Simon Says game. In the REVERIE version, a player tries to follow physical instructions issued by two autonomous agents with different degrees of realism. If a player follows a physical instruction correctly, they are awarded one point. If not, they are deducted one point. This paper presents a technical overview of the game technologies integrated in the Simon Says demo and its evaluation by players with variable computer literacy skills. Finally the potential of REVERIE as an immersive framework for gaming is discussed, followed by recommendations for improvements in future versions of the framework.

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Abstract of paper delivered at the 17th International Reversal Theory Conference, Day 3, session 4, 01.07.15

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This paper reports on the first known empirical use of the Reversal Theory State Measure (RTSM) since its publication by Desselles et al. (2014). The RTSM was employed to track responses to three purposely-selected video commercials in a between-subjects design. Results of the study provide empirical support for the central conceptual premise of reversal theory, the experience of metamotivational reversals and the ability of the RTSM to capture them. The RTSM was also found to be psychometrically sound after adjustments were made to two of its three component subscales. Detailed account and rationale is provided for the analytical process of assessing the psychometric robustness of the RTSM, with a number of techniques and interpretations relating to component structure and reliability discussed. Agreeability and critique of the two available versions of the RTSM – the bundled and the branched – is also examined. Researchers are encouraged to assist development of the RTSM through further use, taking into account the analysis and recommendations presented.