Conceptual network of teachers' talk: Automatic analysis and quantitative measures

  • Daniela Caballero Centre for Advanced Research in Education (CIAE) – University of Chile
  • Toni Pikkarainen University of Jyväskylä
  • Roberto Araya Centre for Advanced Research in Education (CIAE) – University of Chile
  • Jouni Viiri University of Jyväskylä
  • Catalina Espinoza Centre for Advanced Research in Education (CIAE) – University of Chile

Abstract

Educational field can take advantage of the improvements of Automatic Speech Recognition (ASR), since we can apply ASR algorithms in non-ideal conditions such as real classrooms. In the context of [name deleted to maintain the integrity of the review process], conceptual networks are studied. The networks relate key concepts used by the teacher in his/her discourse. In the present study, quantitative metrics are provided, such as centrality measures and PageRank, which can be used to analyse the conceptual networks. With a case-study design, two teachers’ classes are described quantitatively and qualitatively using the metrics, suggesting that PageRank could be a good metric to find differences in teachers’ discourse. Finally, we discuss about the potential of this kind of analysis.

Published
2020-04-28
How to Cite
Caballero, D., Pikkarainen, T., Araya, R., Viiri, J., & Espinoza, C. (2020). Conceptual network of teachers’ talk: Automatic analysis and quantitative measures. FMSERA Journal, 3(1), 18-31. Retrieved from https://journal.fi/fmsera/article/view/79630
Section
Vertaisarvioidut artikkelit