Uncovering what matters: Analyzing transitional relations among contribution types in knowledge-building discourse

Bodong Chen, Monica Resendes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Temporality matters for analysis of collaborative learning. The present study attempts to uncover temporal patterns that distinguish \productive" threads of knowledge building inquiry. Using a rich knowledge building discourse dataset, in which notes' contribution types and threads' productivity have been coded, a secondary temporal analysis was conducted. In particular, Lag-sequential Analysis was conducted to identify transitional patterns among different contribution types that distinguish productive threads from\improvable" ones. Results indicated that productive inquiry threads involved significantly more transitions among questioning, theorizing, obtaining information, and working with information; in contrast, responding to questions and theories by merely giving opinions was not sufficient to achieve knowledge progress. This study highlights the importance of investigating temporality in collaborative learning and calls for attention to developing and testing temporal analysis methods in learning analytics research.

Original languageEnglish (US)
Title of host publicationLAK 2014
Subtitle of host publication4th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages226-230
Number of pages5
ISBN (Print)1595930361, 9781595930361
DOIs
StatePublished - Jan 1 2014
Event4th International Conference on Learning Analytics and Knowledge, LAK 2014 - Indianapolis, IN, United States
Duration: Mar 24 2014Mar 28 2014

Publication series

NameACM International Conference Proceeding Series

Other

Other4th International Conference on Learning Analytics and Knowledge, LAK 2014
Country/TerritoryUnited States
CityIndianapolis, IN
Period3/24/143/28/14

Keywords

  • Collaborative learning
  • Discourse analysis
  • Evidence-based research
  • Knowledge building
  • Lag-sequential analysis
  • Sequential analysis
  • Temporal analysis

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