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.
Original language | English |
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Pages (from-to) | 369-395 |
Number of pages | 27 |
Journal | Journal of Educational Computing Research |
Volume | 56 |
Issue number | 3 |
DOIs | |
Publication status | Published - Jun 2018 |
Externally published | Yes |
Keywords
- bilingual taxonomy of key words
- bilingual text-mining system
- evaluation
- hierarchical visualization
- learner-generated text
ASJC Scopus subject areas
- Education
- Computer Science Applications