719 resultados para games as learning environments


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Social learning approaches have become a prominent focus in studies related to sustainable agriculture. In order to better understand the potential of social learning for more sustainable development, the present study assessed the processes, effects and facilitating elements of interaction related to social learning in the context of Swiss soil protection and the innovative ‘From Farmer - To Farmer’ project. The study reveals that social learning contributes to fundamental transformations of patterns of interactions. However, the study also demonstrates that a learning-oriented understanding of sustainable development implies including analysis of the institutional environments in which the organizations of the individual representatives of face-to-face-based social learning processes are operating. This has shown to be a decisive element when face-to-face-based learning processes of the organisations’ representatives are translated into organisational learning. Moreover, the study revealed that this was achieved not directly through formalisation of new lines of institutionalised cooperation but by establishing links in a ‘boundary space’ trying out new forms of collaboration, aiming at social learning and co-production of knowledge. It is argued that further research on social learning processes should give greater emphasis to this intermediary level of ‘boundary spaces’.

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Second Life (SL) is an ideal platform for language learning. It is called a Multi-User Virtual Environment, where users can have varieties of learning experiences in life-like environments. Numerous attempts have been made to use SL as a platform for language teaching and the possibility of SL as a means to promote conversational interactions has been reported. However, the research so far has largely focused on simply using SL without further augmentations for communication between learners or between teachers and learners in a school-like environment. Conversely, not enough attention has been paid to its controllability which builds on the embedded functions in SL. This study, based on the latest theories of second language acquisition, especially on the Task Based Language Teaching and the Interaction Hypothesis, proposes to design and implement an automatized interactive task space (AITS) where robotic agents work as interlocutors of learners. This paper presents a design that incorporates the SLA theories into SL and the implementation method of the design to construct AITS, fulfilling the controllability of SL. It also presents the result of the evaluation experiment conducted on the constructed AITS.

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It is sometimes unquantifiable how hard it is for most people to deal with game addiction. Several articles have equally been published to address this subject, some suggesting the concept of Educational and serious games. Similarly, researchers have revealed that it does not come easy learning a subject like math. This is where the illusive world of computer games comes in. It is amazing how much people learn from games. In this paper, we have designed and programmed a simple PC math game that teaches rudimentary topics in mathematics.

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In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.

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Person-to-stock order picking is highly flexible and requires minimal investment costs in comparison to automated picking solutions. For these reasons, tradi-tional picking is widespread in distribution and production logistics. Due to its typically large proportion of manual activities, picking causes the highest operative personnel costs of all intralogistics process. The required personnel capacity in picking varies short- and mid-term due to capacity requirement fluctuations. These dynamics are often balanced by employing minimal permanent staff and using seasonal help when needed. The resulting high personnel fluctuation necessitates the frequent training of new pickers, which, in combination with in-creasingly complex work contents, highlights the im-portance of learning processes in picking. In industrial settings, learning is often quantified based on diminishing processing time and cost requirements with increasing experience. The best-known industrial learning curve models include those from Wright, de Jong, Baloff and Crossman, which are typically applied to the learning effects of an entire work crew rather than of individuals. These models have been validated in largely static work environments with homogeneous work contents. Little is known of learning effects in picking systems. Here, work contents are heterogeneous and individual work strategies vary among employees. A mix of temporary and steady employees with varying degrees of experience necessitates the observation of individual learning curves. In this paper, the individual picking performance development of temporary employees is analyzed and compared to that of steady employees in the same working environment.

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Digital game environments are of increasing economic, social and cultural value. As their influence on diverse facets of life grows, states have felt compelled to intervene and secure some public interests. Yet, the contours of a comprehensive governance model are far from recognisable and governments are grappling with the complexity and fluidity of online games and virtual worlds as private spaces and as experimentation fields for creativity and innovation. This book contributes to a more comprehensive and fine-grained understanding of digital game environments, which is a precondition for addressing any of the pressing governance questions posed. Particular attention is given to the concept and policy objective of cultural diversity, which also offers a unique entry point into the discussion of the appropriate legal regulation of digital games. Governance of Digital Game Environments and Cultural Diversity will be of interest to researchers of media law, internet law and governance, cultural studies, anthropology and sociology. As the book addresses a highly topical theme, it will attract the attention of policymakers at national, regional and international levels and will also serve as a great resource tool for scholars in new media and, in particular, digital games and virtual worlds.

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Digital game environments are of increasing economic, social and cultural value. As their influence on diverse facets of life grows, states have felt compelled to intervene and secure some public interests. Yet, the contours of a comprehensive governance model are far from recognisable and governments are grappling with the complexity and fluidity of online games and virtual worlds as private spaces and as experimentation fields for creativity and innovation. This book contributes to a more comprehensive and fine-grained understanding of digital game environments, which is a precondition for addressing any of the pressing governance questions posed. Particular attention is given to the concept and policy objective of cultural diversity, which also offers a unique entry point into the discussion of the appropriate legal regulation of digital games. Governance of Digital Game Environments and Cultural Diversity will be of interest to researchers of media law, internet law and governance, cultural studies, anthropology and sociology. As the book addresses a highly topical theme, it will attract the attention of policymakers at national, regional and international levels and will also serve as a great resource tool for scholars in new media and, in particular, digital games and virtual worlds.

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Despite that a wealth of evidence links striatal dopamine to individualś reward learning performance in non-social environments, the neurochemical underpinnings of such learning during social interaction are unknown. Here, we show that the administration of 300 mg of the dopamine precursor L-DOPA to 200 healthy male subjects influences learning about a partners' prosocial preferences in a novel social interaction task, which is akin to a repeated trust game. We found learning to be modulated by a well-established genetic marker of striatal dopamine levels, the 40-bp variable number tandem repeats polymorphism of the dopamine transporter (DAT1 polymorphism). In particular, we found that L-DOPA improves learning in 10/10R genoype subjects, who are assumed to have lower endogenous striatal dopamine levels and impairs learning in 9/10R genotype subjects, who are assumed to have higher endogenous dopamine levels. These findings provide first evidence for a critical role of dopamine in learning whether an interaction partner has a prosocial or a selfish personality. The applied pharmacogenetic approach may open doors to new ways of studying psychiatric disorders such as psychosis, which is characterized by distorted perceptions of others' prosocial attitudes.

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High precision in motor skill performance, in both sport and other domains (e.g. surgery and aviation), requires the efficient coupling of perceptual inputs (e.g. vision) and motor actions. A particular gaze strategy, which has received much attention within the literature, has been shown to predict both inter- (expert vs. novice) and intra-individual (successful vs. unsuccessful) motor performance (see Vine et al., 2014). Vickers (1996) labelled this phenomenon the quiet eye (QE) which is defined as the final fixation before the initiation of the crucial phase of movement. While the positive influence of a long QE on accuracy has been revealed in a range of different motor skills, there is a growing number of studies suggesting that the relationship between QE and motor performance is not entirely monotonic. This raises interesting questions regarding the QE’s purview, and the theoretical approaches explaining its functionality. This talk aims to present an overview of the issues described above, and to discuss contemporary research and experimental approaches to examining the QE phenomenon. In the first part of the talk Dr. Vine will provide a brief and critical review of the literature, highlighting recent empirical advancements and potential directions for future research. In the second part, Dr. Klostermann will communicate three different theoretical approaches to explain the relationship between QE and motor performance. Drawing upon aspects of all three of these theoretical approaches, a functional inhibition role for the QE (related to movement parameterisation) will be proposed.

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Specification consortia and standardization bodies concentrate on e-Learning objects to en-sure reusability of content. Learning objects may be collected in a library and used for deriv-ing course offerings that are customized to the needs of different learning communities. How-ever, customization of courses is possible only if the logical dependencies between the learn-ing objects are known. Metadata for describing object relationships have been proposed in several e-Learning specifications. This paper discusses the customization potential of e-Learning objects but also the pitfalls that exist if content is customized inappropriately.

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The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.