Learning Analytics for Communities of Inquiry

Authors

  • Vitomir Kovanovic University of Edinburgh
  • Dragan Gasevic University of Edinburgh
  • Marek Hatala Simon Fraser University

DOI:

https://doi.org/10.18608/jla.2014.13.21

Keywords:

Learning analytics, community of inquiry, quantitative content analysis, social network analysis, trace data clustering

Abstract

This paper describes a doctoral research that focuses on the development of a learning analytics framework for inquiry-based digital learning. This research builds on the the Community of Inquiry model (CoI) as a foundation commonly used in research and practice of digital learning and teaching. Specifically, the main contributions of this research are: i) the development of a novel text classification algorithm for (semi)automated message classification which enables for easier adoption of the CoI model, ii) understanding of the relationships between different socio-technological interactions and the dimensions of the CoI model.

Author Biography

Vitomir Kovanovic, University of Edinburgh

Vitomir is a PhD candidate at the School of Informatics at the University of Edinburgh, UK, working under supervision of Professors Dragan Gasevic and Marek Hatala. The focus of his doctoral research is on the development of learning analytics methods for the study of communities of inquiry in online and distance education.

  

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Published

2014-12-24

How to Cite

Kovanovic, V., Gasevic, D., & Hatala, M. (2014). Learning Analytics for Communities of Inquiry. Journal of Learning Analytics, 1(3), 195-198. https://doi.org/10.18608/jla.2014.13.21

Issue

Vol. 1 No. 3 (2014): Widening the Field and Sparks of the Future

Section

Special section: Sparks of the learning analytics future (LASI 2014)

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