Evaluating a bilingual text-mining system with a taxonomy of key words and hierarchical visualization for understanding learner-generated text

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3 Citations (Scopus)

Abstract

This study evaluated a bilingual text-mining system, which incorporated a bilingual taxonomy of key words and provided hierarchical visualization, for understanding learner-generated text in the learning management systems through automatic identification and counting of matching key words. A class of 27 in-service teachers studied a course "e-Learning in primary mathematics" was asked to reflect "what is e-Learning" before and after the course. Their concept of "e-Learning" was investigated by counting the matching key words using the text-mining system and a content analysis of learner-generated text using a rubric, respectively. The correlations of the results using these two methods were .823 and .840 in the preteaching and postteaching reflections. This text-mining system has the potential as a supporting tool for teachers to gain a general understanding of learner-generated text using the hierarchical visualization for supporting pedagogical decision-making, which can be applied to massive open online courses with a large enrolment of learners. Copyright © 2017 The Author(s).
Original languageEnglish
Pages (from-to)369-395
JournalJournal of Educational Computing Research
Volume56
Issue number3
Early online date16 May 2017
Publication statusPublished - 01 Jun 2018

Citation

Kong, S. C., Li, P., & Song, Y. (2018). Evaluating a bilingual text-mining system with a taxonomy of key words and hierarchical visualization for understanding learner-generated text. Journal of Educational Computing Research, 56(3), 369-395. doi: 10.1177/0735633117707991

Keywords

  • Bilingual text-mining system
  • Bilingual taxonomy of key words
  • Evaluation
  • Hierarchical visualization
  • Learner-generated text

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