Automated data analysis to support teacher's knowledge building practice

Abstract

Incorporating asynchronous online discussions as an integral part of introducing knowledge building (KB) in the formal school curriculum poses significant challenges to teachers. Making sense of the sheer volume of students' postings and identifying appropriate facilitation strategies based on these postings is a daunting, if not impossible task even for experienced teachers. This interactive event show cases the work of two research teams that have been developing tools to address teachers' concerns and researchers' interests on students' participation and idea progression in KB discourses. The approach taken by the team comprising researchers from the Centre for Information Technology in Education (CITE), University of Hong Kong and the Center for Knowledge Engineering (CKE), Beijing Normal University is to develop a web-based discourse analysis tool that can provide various forms of participation statistics as well as automatic coding based on linguistic features. The efforts of the Quebec-based team focuses on the use of lexical analysis, using preset lists of concepts or specialized dictionaries, and visualization of latent semantic analysis results.