The Intelligent Helpdesk: Supporting Peer-Help in a University Course

Greer, Jim; McCalla, Gordon I.; Cooke, John; Collins, Jason A.; Kumar, Vive; Bishop, Andrew; Vassileva, Julita

doi:10.1007/3-540-68716-5_55

Cited by 60 publications

(40 citation statements)

References 7 publications

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“…An example of an economic mechanism based on virtual currency can be found in a peer-help community called "I-Help" (Greer et al 1998). The mechanism regulated the demand and supply of help in the community Kostuik and Vassileva 1999).…”

Section: Economic Mechanism Design (Marketplace)mentioning

confidence: 99%

Motivating participation in social computing applications: a user modeling perspective

Vassileva

2012

User Model User-Adap Inter

Self Cite

179

112

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The explosive growth of Web-based social applications over the last 10 years has led people to engage in online communities for various purposes: to work, learn, play, share time and mementos with friends and family and engage in public action. Social Computing Applications (SCA) allow users to discuss various topics in online forums, share their thoughts in blogs, share photos, videos, bookmarks, and connect with friends through social networks. Yet, the design of successful social applications that attract and sustain active contribution by their users still remains more of an art than a science. My research over the last 10 years has been based on the hypothesis that it is possible to incorporate mechanisms and tools in the design of the social application that can motivate users to participate, and more generally, to change their behavior in a desirable way, which is beneficial for the community. Since different people are motivated by different things, it can be expected that personalizing the incentives and the way the rewards are presented to the individual, would be beneficial. Also since communities have different needs in different phases of their existence, it is necessary to model the changing needs of communities and adapt the incentive mechanisms accordingly, to attract the kind of contributions that are beneficial. Therefore User and Group (Community) Modeling is an important area in the design of incentive mechanisms. This paper presents an overview of different approaches to motivate users to participate. These approaches are based on various theories from the area of social psychology and behavioral economics and involve rewards mechanisms, reputation, open group user modeling, and social visualization. Future trends are outlined towards convergence with the areas of persuasive systems design, adaptive/personalized systems, and intelligent social learning environments.

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Section: Economic Mechanism Design (Marketplace)mentioning

confidence: 99%

Motivating participation in social computing applications: a user modeling perspective

Vassileva

2012

User Model User-Adap Inter

Self Cite

179

112

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“…This research community has explored how we can design adaptive technology that takes a learner's context and potential collaborators into account (Greer, McCalla, Cooke, Collins, Kumar, Bishop, andVassileva, 1998, andMurray andArroyo, 2002, for example). By moving beyond the desktop and outside the classroom context, wireless, mobile and ubiquitous technologies have been shown to engage learners in hands-on experience and activities in real world learning situations.…”

Section: What Is Context?mentioning

confidence: 99%

Using Mobile Technology to Create Flexible Learning Contexts

Luckin¹,

Boulay²,

Smith³

et al. 2005

JIME

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“…For example, Purpose-1 could be adapted for the domain of peer help (Greer et a., 1998; to choose a helper for a student who needs some help.…”

Section: Purpose Re -Usementioning

confidence: 99%

Purpose‐Based Expert Finding in a Portfolio Management System

Niu

McCalla

Vassileva

2004

Computational Intelligence

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Abstract. Most of the research in the area of expert finding focuses on creating and maintaining centralized directories of experts' profiles, which users can search on demand. However, in a distributed multi-agent based software environment, the autonomous agents are free to develop expert models or model fragments for their own purposes and from their viewpoints. Therefore the focus of expert finding is shifting from the collection at one place as much data about a expert as possible to accessing on demand from various agents whatever user information is available at the moment and interpreting it for a particular purpose. This paper outlines purpose-based expert modelling as an approach for finding an expert in a multi-agent portfolio management system in which autonomous agents develop expert agent models independently and do not adhere to a common representation scheme. This a pproach aims to develop taxonomy of purposes that define a variety of context-dependent user modelling processes which are used by the users' personal agents to find appropriate expert agents to advise users on investing strategies.

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The Intelligent Helpdesk: Supporting Peer-Help in a University Course

Cited by 60 publications

References 7 publications

Motivating participation in social computing applications: a user modeling perspective

Motivating participation in social computing applications: a user modeling perspective

Using Mobile Technology to Create Flexible Learning Contexts

Purpose‐Based Expert Finding in a Portfolio Management System

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