From Mirroring to Guiding: A Review of State of the Art Technology for Supporting Collaborative Learning

  • Authors:

  • Amy Soller;Alejandra Martínez;Patrick Jermann;Martin Muehlenbrock

  • Affiliations:

  • Institute for Defense Analyses, 4850 Mark Center Drive, Alexandria, VA 22311, USA. E-mail: asoller@ida.org;Department of Computer Science, University of Valladolid, 47011 Valladolid, Spain. E-mail: amartine@infor.uva.es;Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland. E-mail: Patrick.Jermann@epfl.ch;DFKI, German Research Center for Artificial Intelligence, 66123 Saarbruecken, Germany. E-mail: Martin.Muehlenbrock@dfki.de

  • Venue:
  • International Journal of Artificial Intelligence in Education
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We review a representative selection of systems that support the management of collaborative learning interaction, and characterize them within a simple classification framework. The framework distinguishes between mirroring systems, which display basic actions to collaborators, metacognitive tools, which represent the state of interaction via a set of key indicators, and coaching systems, which offer advice based on an interpretation of those indicators. The reviewed systems are further characterized by the type of interaction data they assimilate, the processes they use for deriving higher-level data representations, the variables or indicators that characterize these representations, and the type of feedback they provide to students and teachers. This overview of technological capabilities is designed to lay the groundwork for further research into which technological solutions are appropriate for which learning situations.