Effects of speech-to-text recognition application on learning performance in synchronous cyber classrooms

Wu Yuin Hwang, Rustam Shadiev, Tony C.T. Kuo, Nian Shing Chen

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

The aim of this study was to apply Speech-to-Text Recognition (STR) in an effort to improve learning performance in an online synchronous cyber classroom environment. Students' perceptions and their behavioral intentions toward using STR and the effectiveness of applying STR in synchronous cyber classrooms were also investigated. After the experiment, students from the experimental group perceived that the STR mechanism was easy to use and useful for one-way lectures as well as for individual learning. Most students also expressed that they were highly motivated to use STR as a learning tool in the future. Statistical results showed moderate improvement in the experimental groups' performance over the control group on homework accomplishments. However, once the students in the experimental group became familiar with the STR-generated texts and used them as learning tools, they significantly outperformed the control group students in post-test results. Interviews with participating students revealed that STR-generated texts were beneficial to learning during and after oneway lectures. Based on our findings, it is recommended that students apply STR to enhance their understanding of teachers' lectures in an online synchronous cyber classroom. Additionally, we recommend students should take advantages of the text generated by STR both during and after lectures.

Original languageEnglish
Pages (from-to)367-380
Number of pages14
JournalEducational Technology and Society
Volume15
Issue number1
StatePublished - 2012

Keywords

  • Homework
  • Note-taking
  • Speech to text recognition
  • Synchronous learning

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