860 research outputs found

    A comparison of methodological frameworks for digital learning game design

    Get PDF
    Methodological frameworks guide the design of digital learning game based on well founded learning theories and instructional strategies. This study presents a comparison of five methodological frameworks for digital learning game design, highlighting their similarities and differences. The objective is to support the choice of an adequate framework, aiming to promote them as a way to foster principled digital learning games design. This paper concludes that: (i) interactivity, engagement and increasing complexity of challenges are fundamental factors to digital learning game design; (ii) the pedagogical base, the target, the possibility of doing game assessment and the presence of practical guidelines are the selection criteria that influence most the choice of a methodological framework, and (iii) the development of digital learning games - preferably by different research teams - is needed to provide empirical evidence of the utility of framework-based design

    Impact of socioeconomic deprivation on rate and cause of death in severe mental illness

    Get PDF
    Background: Socioeconomic status has important associations with disease-specific mortality in the general population. Although individuals with Severe Mental Illnesses (SMI) experience significant premature mortality, the relationship between socioeconomic status and mortality in this group remains under investigated.<p></p> Aims: To assess the impact of socioeconomic status on rate and cause of death in individuals with SMI (schizophrenia and bipolar disorder) relative to the local (Glasgow) and wider (Scottish) populations.<p></p> Methods: Cause and age of death during 2006-2010 inclusive for individuals with schizophrenia or bipolar disorder registered on the Glasgow Psychosis Clinical Information System (PsyCIS) were obtained by linkage to the Scottish General Register Office (GRO). Rate and cause of death by socioeconomic status, measured by Scottish Index of Multiple Deprivation (SIMD), were compared to the Glasgow and Scottish populations.<p></p> Results: Death rates were higher in people with SMI across all socioeconomic quintiles compared to the Glasgow and Scottish populations, and persisted when suicide was excluded. Differences were largest in the most deprived quintile (794.6 per 10,000 population vs. 274.7 and 252.4 for Glasgow and Scotland respectively). Cause of death varied by socioeconomic status. For those living in the most deprived quintile, higher drug-related deaths occurred in those with SMI compared to local Glasgow and wider Scottish population rates (12.3% vs. 5.9%, p = <0.001 and 5.1% p = 0.002 respectively). A lower proportion of deaths due to cancer in those with SMI living in the most deprived quintile were also observed, relative to the local Glasgow and wider Scottish populations (12.3% vs. 25.1% p = 0.013 and 26.3% p = <0.001). The proportion of suicides was significantly higher in those with SMI living in the more affluent quintiles relative to Glasgow and Scotland (54.6% vs. 5.8%, p = <0.001 and 5.5%, p = <0.001). Discussion and conclusions: Excess mortality in those with SMI occurred across all socioeconomic quintiles compared to the Glasgow and Scottish populations but was most marked in the most deprived quintiles when suicide was excluded as a cause of death. Further work assessing the impact of socioeconomic status on specific causes of premature mortality in SMI is needed

    Automated Adaptation and Assessment inĀ Serious Games: A Portable Tool forĀ SupportingĀ Learning

    Get PDF
    We introduce the Adaptation and Assessment (TwoA) component, an open-source tool for serious games, capable of adjusting game difficulty to player skill level. Technically, TwoA is compliant with the RAGE (Horizon 2020) game component architecture, which offers seamless portability to a variety of popular game development platforms. Conceptually, TwoA uses a modified version of the Computer Adaptive Practice algorithm. Our version offers two improvements over the original algorithm. First, the TwoA improves balancing of player's motivation and game challenge. Second, TwoA reduces the selection bias that may arise for items of similar difficulty by adopting a fuzzy selection rule. These improvements are validated using multi-agent simulations.This study is part of the RAGE project. The RAGE project has received funding from the European Unionā€™s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains

    Predicting video game playersā€™ fun from physiological and behavioural data : one algorithm does not fit all

    Get PDF
    Finding a physiological signature of a playerā€™s fun is a goal yet to be achieved in the field of adaptive gaming. The research presented in this paper tackles this issue by gathering physiological, behavioural and self-report data from over 200 participants who played off-the-shelf video games from the Assassinā€™s Creed series within a minimally invasive laboratory environment. By leveraging machine learning techniques the prediction of the playerā€™s fun from its physiological and behavioural markers becomes a possibility. They provide clues as to which signals are the most relevant in establishing a physiological signature of the fun factor by providing an important score based on the predictive power of each signal. Identifying those markers and their impact will prove crucial in the development of adaptive video games. Adaptive games tailor their gameplay to the affective state of a player in order to deliver the optimal gaming experience. Indeed, an adaptive video game needs a continuous reading of the fun level to be able to respond to these changing fun levels in real time. While the predictive power of the presented classifier remains limited with a gain in the F1 score of 15% against random chance, it brings insight as to which physiological features might be the most informative for further analysis and discuss means by which low accuracy classification could still improve gaming experience

    FILTWAM and Voice Emotion Recognition

    Get PDF
    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone data for a real-time and adequate interpretation of vocal expressions into emotional states were the software is calibrated with end users. FILTWAM already incorporates a valid face emotion recognition module and is extended with a voice emotion recognition module. This extension aims to provide relevant and timely feedback based upon learner's vocal intonations. The feedback is expected to enhance learnerā€™s awareness of his or her own behavior. Six test persons received the same computer-based tasks in which they were requested to mimic specific vocal expressions. Each test person mimicked 82 emotions, which led to a dataset of 492 emotions. All sessions were recorded on video. An overall accuracy of our software based on the requested emotions and the recognized emotions is a pretty good 74.6% for the emotions happy and neutral emotions; but will be improved for the lower values of an extended set of emotions. In contrast with existing software our solution allows to continuously and unobtrusively monitor learnersā€™ intonations and convert these intonations into emotional states. This paves the way for enhancing the quality and efficacy of game-based learning by including the learner's emotional states, and links these to pedagogical scaffolding.The Netherlands Laboratory for Lifelong Learning (NELLL) of the Open University of the Netherlands

    Computers in Secondary Schools: Educational Games

    Full text link
    This entry introduces educational games in secondary schools. Educational games include three main types of educational activities with a playful learning intention supported by digital technologies: educational serious games, educational gamification, and learning through game creation. Educational serious games are digital games that support learning objectives. Gamification is defined as the use of "game design elements and game thinking in a non-gaming context" (Deterding et al. 2011, p. 13). Educational gamification is not developed through a digital game but includes game elements for supporting the learning objectives. Learning through game creation is focused on the process of designing and creating a prototype of a game to support a learning process related to the game creation process or the knowledge mobilized through the game creation process. Four modalities of educational games in secondary education are introduced in this entry to describe educational games in secondary education: educational purpose of entertainment games, serious games, gamification, and game design

    Differential Response of Primary and Immortalized CD4+ T Cells to Neisseria gonorrhoeae-Induced Cytokines Determines the Effect on HIV-1 Replication

    Get PDF
    To compare the effect of gonococcal co-infection on immortalized versus primary CD4+ T cells the Jurkat cell line or freshly isolated human CD4+ T cells were infected with the HIV-1 X4 strain NL4-3. These cells were exposed to whole gonococci, supernatants from gonococcal-infected PBMCs, or N. gonorrhoeae-induced cytokines at varying levels. Supernatants from gonococcal-infected PBMCs stimulated HIV-1 replication in Jurkat cells while effectively inhibiting HIV-1 replication in primary CD4+ T cells. ELISA-based analyses revealed that the gonococcal-induced supernatants contained high levels of proinflammatory cytokines that promote HIV-1 replication, as well as the HIV-inhibitory IFNĪ±. While all the T cells responded to the HIV-stimulatory cytokines, albeit to differing degrees, the Jurkat cells were refractory to IFNĪ±. Combined, these results indicate that N. gonorrhoeae elicits immune-modulating cytokines that both activate and inhibit HIV-production; the outcome of co-infection depending upon the balance between these opposing signals
    • ā€¦
    corecore