Designing tabletop-based systems for user modelling of collaboration

Roberto Martinez, Christopher Ackad, Judy Kay, Kalina Yacef

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

Tabletops offer a new form of interaction and create new possibilities for small groups of people to collaborate and discuss tasks aided by the shared use of digital materials and tools. The collaborative affordances of tabletops make them suitable for many uses in public spaces as well as in more restricted environments such as workplaces and learning settings. This creates new opportunities for improving collaboration, particularly by capturing data that can be used to model the nature of the interactions and to present this model to the users in a form that will facilitate improved collaboration. It is timely to establish principles for designing tabletop-based systems in a manner that can facilitate such modelling. These principles should support effective use of data mining tools to create group collaboration models. In this paper, we outline theoretical design principles based on a careful analysis of the nature of tabletop datasets and collaboration.

Original languageEnglish
Title of host publicationInternational Workshop on Adaptive Support for Team Collaboration 2011, ASTC 2011
PublisherRheinisch-Westfaelische Technische Hochschule Aachen
Pages47-51
Number of pages5
Publication statusPublished - 2011
Externally publishedYes
EventInternational Workshop on Adaptive Support for Team Collaboration 2011, ASTC 2011 - Held in Conjunction with the 19th International Conference on User Modeling, Adaptation and Personalization, UMAP 2011 - Girona, Spain
Duration: 15 Jul 201115 Jul 2011

Conference

ConferenceInternational Workshop on Adaptive Support for Team Collaboration 2011, ASTC 2011 - Held in Conjunction with the 19th International Conference on User Modeling, Adaptation and Personalization, UMAP 2011
Country/TerritorySpain
CityGirona
Period15/07/1115/07/11

Keywords

  • Collaborative learning
  • Collocated collaboration
  • Group modelling
  • Interactive tabletops
  • Machine learning

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