Agent-based architectural framework enhancing configurability, autonomy and scalability of context-aware pervasive services

Dimakis, N.; Soldatos, John; Polymenakos, Lazaros; Bürkle, Axel; Pfirrmann, Uwe; Sutschet, Gerhard

doi:10.1007/s10458-009-9101-1

Cited by 4 publications

(4 citation statements)

References 40 publications

(43 reference statements)

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“…The User Profile is a central component of the MASELTOV platform that makes use of a backend database for storing, logging and maintaining information about personal data and user preferences, as well as collected knowledge on usage behaviour, progress and user context recognition (Dimakis et al, 2010). In this way, it enables the personalization of used services, for example triggering of personalized recommendations on MASELTOV functionalities, targeted services and assistance (Figure 2).…”

Section: Overall Design Conceptmentioning

confidence: 99%

Mobile Incidental Learning to Support the Inclusion of Recent Immigrants

Kukulska‐Hulme¹,

Gaved²,

Paletta³

et al. 2015

Ubiquitous Learning: An International Journal

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Section: Overall Design Conceptmentioning

confidence: 99%

Mobile Incidental Learning to Support the Inclusion of Recent Immigrants

Kukulska‐Hulme¹,

Gaved²,

Paletta³

et al. 2015

Ubiquitous Learning: An International Journal

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“…Maseltov embeds an easily scalable context-recognition framework 31 that receives input from various context-generating components, such as modules that indicate a current location or the level of learning a host language. The framework evaluates the user's behavior and maps it to appropriately motivating actions in the form of recommendations.…”

Section: Social Inclusion and Empowerment Of Immigrantsmentioning

confidence: 99%

Serious Gaming for Behavior Change: The State of Play

Schuller

Dunwell

Weninger

et al. 2013

IEEE Pervasive Comput.

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U n d e r s t a n d i n g a n d C h a n g i n g B e h a v i o r serious gaming for Behavior Change: the state of Play S erious gaming is often described as the use of digital gaming technology to address a specific set of learning objectives or behavioral goals. Such games seek to build on the increasingly pervasive role games play as an entertainment medium, providing an engaging and entertaining way of communicating educational content along with efficient behavior analysis. As Richard Lingard once said, "If you would read a man's Disposition, see him Game; you will then learn more of him in one hour, than in seven Years [of] Conversation." 1 In this sense, serious games hold great promise for behavior analysis of human players. Moreover, they can encourage positive behavior change in a playful and pleasant way-something games have sought to achieve in a variety of ways. Common is the central role the game plays as either a medium for conveying educational messages or for encouraging certain activities through game-based elements, such as competition or rewards. However, a significant challenge has been getting the players to apply the changed behavior in the real world. Pervasive computing can help overcome this gap, letting players at times learn the behavior in the environment in which it must be applied.Furthermore, although serious games show great application potential for individuals on the autistic spectrum or for other target groups that experience difficulties in human-to-human communication, current games for behavior change rarely address human-to-human interaction. This would require a holistic approach that takes into account behavioral cues from multisensory input-possibly including speech, video (facial expressions and gestures), and physiological sensors.In this light, we first examine the state of play in serious games, focusing on affective analysis-that is, the recognition and analysis of players' emotions. We then present two exemplary case studies from the context of teaching appropriate behavior in human-to-human interaction and consider how to exploit mobile computing for automatic, multimodal analysis of human behavior. Behavior analysis and FeedbackHere, we explore how knowledge transfer, gamification, and social learning can help induce behavioral change. Two unique traits of games make them particularly interesting as tools for analyzing and changing player behaviors. The first is their universal appeal and ability to reach certain demographics traditionally resistant to other forms of direct messaging or intervention, such as adolescents. The second Serious gaming guides targeted behavior change to improve behaviors in everyday living. This survey of the field focuses on two case studiesone game aims to improve the social behavior of autistic children, and the other helps migrants interact with locals.

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“…MASELTOV embeds an easily scalable context recognition framework (Dimakis et al, 2010) that receives contributions from various context feature generating services; it evaluates the user behavior and from this maps to appropriately motivating actions in the form of recommendations. In MASELTOV, user behavior is evaluated in terms of progress indicators in the frame of the various services.…”

Section: Geo-contextual Context Sensing and Classificationmentioning

confidence: 99%

Advances in MASELTOV – Serious Games in a Mobile Ecology of Services for Social Inclusion and Empowerment of Recent Immigrants

Paletta

Dunwell

Gaved

et al. 2013

Lecture Notes in Computer Science

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Immigration imposes a range of challenges with the risk of social exclusion. As part of a comprehensive suite of services for immigrants, the MASELTOV game seeks to provide both practical tools and innovative learning services via mobile devices, providing a readily usable resource for recent immigrants. We introduce advanced results, such as the game-based learning aspect in the frame of recommender services, and present the rationale behind its interaction design. Benefits and implications of mobile platforms and emergent data capture techniques for game-based learning are discussed, as are methods for putting engaging gameplay at the forefront of the experience whilst relying on rich data capture and analysis to provide effective learning solutions.Keywords. Mobile serious game, social inclusion, incidental learning framework, recommender system, human factors. Geo-social radar:A volunteer helper service allowing users to find nearby volunteers who can help them with a problem, for example acting as a translator at a doctor's appointment, or negotiating local bureaucracy.TextLens: allows a learner to take a photo of a sign, and have this converted to text. This can then be coupled with a language translation tool such as Google Translate. Images and text can be uploaded for help when the meaning is ambiguous, and if the learner wishes to discuss their social, cultural or legal implications.

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Agent-based architectural framework enhancing configurability, autonomy and scalability of context-aware pervasive services

Cited by 4 publications

References 40 publications

Mobile Incidental Learning to Support the Inclusion of Recent Immigrants

Mobile Incidental Learning to Support the Inclusion of Recent Immigrants

Serious Gaming for Behavior Change: The State of Play

Advances in MASELTOV – Serious Games in a Mobile Ecology of Services for Social Inclusion and Empowerment of Recent Immigrants

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