5,835 research outputs found

    A GRAPH-BASED APPROACH FOR ADAPTIVE SERIOUS GAMES

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    Traditional education systems are based on the one-size-fits-all approach, which lacks personalization, engagement, and flexibility necessary to meet the diverse needs and learning styles of students. This encouraged researchers to focus on exploring automated, personalized instructional systems to enhance students’ learning experiences. Motivated by this remark, this thesis proposes a personalized instructional system using a graph method to enhance a player’s learning process by preventing frustration and avoiding a monotonous experience. Our system uses a directional graph, called an action graph, for representing solutions to in-game problems based on possible player actions. Through our proposed algorithm, a serious game integrated with our system would both detect player errors and provide personalized assistance to direct a player in the direction of a correct solution. To verify system performance, this research presents comparison testing on a group of students engaging in the game both with and without AI. Students who played the AI-assisted game showed an average 20% decrease in time needed and an average 58% decrease in actions taken to complete the game

    Countdown VR: a Serious Game in Virtual Reality to Develop Mental Computation Skills

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    Virtual reality (VR) can be utilized to create video games exploring novel ways to control and interact with the environment. VR can be employed to revisit, extend, and enhance old video games to give them a new lease of life. In this paper, we describe the game Countdown VR in which players must use mental computation to reach a target number. Mental computation is used in everyday life, it is used for quick calculations and estimations. Countdown VR is a serious game designed and implemented using the Learning Mechanics-Game Mechanics framework. We provide an analysis of different approaches for determining the difficulty level of the game based on a number and target to attain and a selection of numbers combined to reach the target. We assess the user's performance and user's experience in the game, with questionnaires to quantify the related workload, usability, flow, motivation, and potential symptoms of users playing the game. The results provide key information related to the relationships between the subjective and objective evaluations of the proposed VR game by players, with a high correlation between VR sickness questionnaires, and moderate correlations between usability and motivation, flow and motivation

    Adaptive Augmented Reality Serious Game to Foster Problem Solving Skills

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    This paper describes the design of an adaptive intelligent augmented reality serious game which aims to foster problem solving skills in young learners. Studies show that our students lack computational thinking skills in high school, which raises the need to establish new methods to develop these skills in our younger learners. We believe that problem solving skills are the fundamental skills of computational thinking and are critical for STEM, in addition to a broad range of other fields. Therefore we decided to focus on those meta-cognitive skills acquired to foster problem solving, such as strategic knowledge. The game described in this paper provides a unique adaptive learning environment that aims to develop learners’ meta-cognitive skills by utilizing augmented reality technology, believable pedagogical agents and intelligent tutoring modules. It offers a great user experience and entertainment which we hope will encourage learners to invest more time in the learning process. This paper describes the architecture and design of the game from the viewpoint of educational pedagogies and frameworks for serious game design

    An Overview of Self-Adaptive Technologies Within Virtual Reality Training

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    This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

    Integrating the strengths of cognitive emotion models with traditional HCI analysis tools

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    This paper reports an attempt to integrate key concepts from cognitive models of emotion to cognitive models of interaction established in HCI literature. The aim is to transfer the strengths of interaction models to analysis of affect-critical systems in games, e-commerce and education, thereby increasing their usefulness in these systems where affect is increasingly recognised as a key success factor. Concepts from Scherer’s appraisal model and stimulation evaluation checks, along with a framework of emotion contexts proposed by Coulson (An everything but framework for modelling emotion. In proceeding of AAAI spring symposium on architectures for emotion, 2004), are integrated into the cycle of display-based action proposed by Norman (The design of everyday things. Basic Books, New York, 1988). Norman’s action cycle has commonly been applied as an interaction analysis tool in the field of HCI. In the wake of the recent shift of emphasis to user experience, the cognition-based action cycle is deemed inadequate to explicate affective experiences, such as happiness, joy and surprise. Models based on appraisal theories, focusing on cognitive accounts of emotion, are more relevant to understanding the causes and effects of feelings arising from interacting with digital artefacts. The paper explores the compatibility between these two genres of model, and future development of integrated analysis tools

    Integrating the strengths of cognitive emotion models with traditional HCI analysis tools

    Get PDF
    This paper reports an attempt to integrate key concepts from cognitive models of emotion to cognitive models of interaction established in HCI literature. The aim is to transfer the strengths of interaction models to analysis of affect-critical systems in games, e-commerce and education, thereby increasing their usefulness in these systems where affect is increasingly recognised as a key success factor. Concepts from Scherer’s appraisal model and stimulation evaluation checks, along with a framework of emotion contexts proposed by Coulson (An everything but framework for modelling emotion. In proceeding of AAAI spring symposium on architectures for emotion, 2004), are integrated into the cycle of display-based action proposed by Norman (The design of everyday things. Basic Books, New York, 1988). Norman’s action cycle has commonly been applied as an interaction analysis tool in the field of HCI. In the wake of the recent shift of emphasis to user experience, the cognition-based action cycle is deemed inadequate to explicate affective experiences, such as happiness, joy and surprise. Models based on appraisal theories, focusing on cognitive accounts of emotion, are more relevant to understanding the causes and effects of feelings arising from interacting with digital artefacts. The paper explores the compatibility between these two genres of model, and future development of integrated analysis tools
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