European Resuscitation Council Guidelines for Resuscitation.

The Social Psychology of Groups. J. W Thibaut & H. H. Kelley. New York: alley, 1959. The team of Thibaut and Kelley goes back to 1946 when, after serving in different units of the armed services psychology program, the authors joined the Research Center for Group Dynamics, first at M.LT and then at the University of Michigan. Their continued association eventuated in appointments as fellows at the Center for Advanced Study in the Behavioral Sciences, 19561957. It is during these years that their collaboration resulted in the publication of The Social Psychology of Groups. The book was designed to "bring order and coherence to present-day research in interpersonal relations and group functioning." To accomplish this aim, the authors introduced, defined, and illustrated basic concepts in an effort to explain the simplest of social phenomena, the two-person relationship. These basic principles and concepts were then employed to illuminate larger problems and more complex social relationships and to examine the significance of such concepts as roles, norm, power, group cohesiveness, and status. The lasting legacy of this book is derived from the fact that the concepts and principles discussed therein serve as a foundation for one of the dominant conceptual frameworks in the field of family studies today-the social exchange framework. Specifically, much of our contemporary thinking about the process of interpersonal attraction and about how individuals evaluate their close relationships has been influenced by the theory and concepts introduced in The Social Psychology of Groups. Today, as a result of Thibaut and Kelley, we think of interpersonal attraction as resulting from the unique valence of driving and restraining forces, rewards and costs, subjectively thought to be available from a specific relationship and its competing alternatives. We understand, as well, that relationships are evaluated through complex and subjectively based comparative processes. As a result, when we think about assessing the degree to which individuals are satisfied with their relationships, we take into consideration the fact that individuals differ in terms of the importance they attribute to different aspects of a relationship (e.g., financial security, sexual fulfillment, companionship). We also take into consideration the fact that individuals differ in terms of the levels of rewards and costs that they believe are realistically obtainable and deserved from a relationship. In addition, as a result of Thibaut and Kelley's theoretical focus on the concept of dependence and the interrelationship between attraction and dependence, there has evolved within the field of family studies a deeper appreciation for the complexities and variability found within relationships. Individuals are dependent on their relationships, according to Thibaut and Kelley, when the outcomes derived from the existing relationship exceed those perceived to be available in competing alternatives. Individuals who are highly dependent on their relationships are less likely to act to end their relationships. This dependence and the stability it engenders may or may not be voluntary, depending on the degree to which individuals are attracted to and satisfied with their relationships. When individuals are both attracted to and dependent on their relationships, they can be thought of as voluntarily participating in their relationship. That is, they are likely to commit themselves to the partner and relationship and actively work for its continuance. Thibaut and Kelley termed those relationships characterized by low levels of satisfaction and high levels of dependence "nonvoluntary relationships. …

The Social Psychology of Groups

Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermedia and user modeling. Adaptive hypermedia systems build a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user. The goal of this paper is to present the state of the art in adaptive hypermedia at the eve of the year 2000, and to highlight some prospects for the future. This paper attempts to serve both the newcomers and the experts in the area of adaptive hypermedia by building on an earlier comprehensive review (Brusilovsky, 1996; Brusilovsky, 1998).

Adaptive Hypermedia

A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management. Various recommender system techniques have been proposed since the mid-1990s, and many sorts of recommender system software have been developed recently for a variety of applications. Researchers and managers recognize that recommender systems offer great opportunities and challenges for business, government, education, and other domains, with more recent successful developments of recommender systems for real-world applications becoming apparent. It is thus vital that a high quality, instructive review of current trends should be conducted, not only of the theoretical research results but more importantly of the practical developments in recommender systems. This paper therefore reviews up-to-date application developments of recommender systems, clusters their applications into eight main categories: e-government, e-business, e-commerce/e-shopping, e-library, e-learning, e-tourism, e-resource services and e-group activities, and summarizes the related recommendation techniques used in each category. It systematically examines the reported recommender systems through four dimensions: recommendation methods (such as CF), recommender systems software (such as BizSeeker), real-world application domains (such as e-business) and application platforms (such as mobile-based platforms). Some significant new topics are identified and listed as new directions. By providing a state-of-the-art knowledge, this survey will directly support researchers and practical professionals in their understanding of developments in recommender system applications. Research papers on various recommender system applications are summarized.The recommender systems are examined systematically through four dimensions.The recommender system applications are classified into eight categories.Related recommendation techniques in each category are identified.Several new recommendation techniques and application areas are uncovered.

Recommender system application developments

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The Cambridge Handbook Of The Learning Sciences

Recommender systems have been researched extensively by the Technology Enhanced Learning (TEL) community during the last decade. By identifying suitable resources from a potentially overwhelming variety of choices, such systems offer a promising approach to facilitate both learning and teaching tasks. As learning is taking place in extremely diverse and rich environments, the incorporation of contextual information about the user in the recommendation process has attracted major interest. Such contextualization is researched as a paradigm for building intelligent systems that can better predict and anticipate the needs of users, and act more efficiently in response to their behavior. In this paper, we try to assess the degree to which current work in TEL recommender systems has achieved this, as well as outline areas in which further work is needed. First, we present a context framework that identifies relevant context dimensions for TEL applications. Then, we present an analysis of existing TEL recommender systems along these dimensions. Finally, based on our survey results, we outline topics on which further research is needed.

Context-Aware Recommender Systems for Learning: A Survey and Future Challenges

This article introduces learning analytics dashboards that visualize learning traces for learners and teachers. We present a conceptual framework that helps to analyze learning analytics applications for these kinds of users. We then present our own work in this area and compare with 15 related dashboard applications for learning. Most evaluations evaluate only part of our conceptual framework and do not assess whether dashboards contribute to behavior change or new understanding, probably also because such assessment requires longitudinal studies.

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Learning analytics dashboard applications

Katholieke Universiteit Leuven, Belgium Erik DuvalErik.Duval@cs.kuleuven.ac.beStrategic FuturistAutodesk Wayne Hodginswayne.hodgins@autodesk.comAssociate Professor, The Information SchoolUniversity of Washington Stuart Suttonsasutton@u.washington.eduExecutive DirectorDublin Core Metadata Initiative Stuart L. WeibelWeibel@oclc.org

Metadata Principles and Practicalities

In this paper, we present work on learning analytics that aims to support learners and teachers through dashboard applications, ranging from small mobile applications to learnscapes on large public displays. Dashboards typically capture and visualize traces of learning activities, in order to promote awareness, reflection, and sense-making, and to enable learners to define goals and track progress toward these goals. Based on an analysis of our own work and a broad range of similar learning dashboards, we identify HCI issues for this exciting research area.

/pdf/learning-dashboards-an-overview-and-future-research-1hgcl78tf0.pdf

Learning dashboards: an overview and future research opportunities

This paper will present the general goal of and inspiration for our work on learning analytics, that relies on attention metadata for visualization and recommendation. Through information visualization techniques, we can provide a dashboard for learners and teachers, so that they no longer need to "drive blind". Moreover, recommendation can help to deal with the "paradox of choice" and turn abundance from a problem into an asset for learning.

/pdf/attention-please-learning-analytics-for-visualization-and-3a8ofw9jze.pdf

Erik Duval

Papers

Context-Aware Recommender Systems for Learning: A Survey and Future Challenges

Learning analytics dashboard applications

Metadata Principles and Practicalities

Learning dashboards: an overview and future research opportunities

Attention please!: learning analytics for visualization and recommendation