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Classification techniques for assessing student collaboration in shared wiki spaces

  • Chitrabharathi Ganapathy
  • , Jeon Hyung Kang
  • , Erin Shaw
  • , Jihie Kim
  • University of Southern California

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

2 Scopus citations

Abstract

This paper presents the case study of collaboration analysis in the context of an undergraduate student engineering project. Shared Wiki spaces used by students in collaborative project teams were analyzed and the paper presents new techniques, based on descriptive statistics and the Labeled Latent Dirichlet Allocation (LLDA) model for multi-label document classification, to assess quality of student work in shared wiki spaces. A link is shown between processes of collaboration, performance and work pace.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education - 15th International Conference, AIED 2011
PublisherSpringer Verlag
Pages456-458
Number of pages3
ISBN (Print)9783642218682
DOIs
StatePublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6738 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Collaborative learning assessment
  • Descriptive Statistics
  • Labeled Latent Dirichlet Allocation
  • Topic Modeling
  • Wiki Assessment

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