edit Process Mining to Support Collaborative Writing

Process Mining to Support Collaborative Writing

Vilaythong Southavilay, Kalina Yacef and Rafael A. Calvo
School of Information Technologies, University of Sydney

Contact Person

Vilaythong Southavilay
vstoto@it.usyd.edu.au

Project Description

Computer-Supported Collaborative Writing has received attention since computers have been used for word processing. Due to the availability of the Internet, people increasingly write collaboratively by sharing their documents in a number of ways. Writing individually and collaboratively are considered essential skills in most industries, academia, and government. This has led to increased research on how to support the production of better documents.

Over the past two decades, there has been abundant text-mining research for improving the support of quality writing. But work such as automatic scoring of essay, visualization, and document clustering focus on the final product, not on the writing process itself. Investigating how ideas and concepts are developed during the process of writing could be used to improve not only the quality of the documents but more importantly the writing skills of those involved.

Our project aim is to investigate and develop techniques to support collaborative writing activities by providing feedback to students during the collaborative writing process. To achieve this, we will:
  • Develop a new framework for exploring collaborative writing process.
  • Investigate and identify techniques to extract the semantic meaning of text changes during collaborative writing, based on semantic analysis.
  • Examine and develop novel techniques to discover sequence patterns of writing activities that lead to successful outcome and those that may lead to problems, based on process analysis.
  • Design and develop efficient and effective techniques to provide feedback on and/or visualization of writing process.

  • Key Publications

    V. Southavilay, K. Yacef, and R. A. Calvo. Process mining to support students’ collaborative writing (best student paper award). In Educational Data Mining conference proceedings, pages 257-266, 2010. [View Details]

    V. Southavilay, K. Yacef, and R. A. Calvo. Analysis of collaborative writing processes using hidden markov models and semantic heuristics. In Submitted to Workshop on Semantic Aspects in Data Mining (SADM) at ICDM2010, pages 543-548, 2010. [View Details]