Skip to main content
AkademIndex

Products

For developers

AkademBasesoonOpen API for the ecosystem
Latin
English
Article

Investigating Visual Attention of Students with Different Learning Ability on Texts Generated by Speech-to-Text Recognition

Rustam ShadievDepartment of Engineering Science, National Cheng Kung University, TaiwanYueh‐Min HuangDepartment of Engineering Science, National Cheng Kung University, TaiwanWu‐Yuin HwangGraduate Institute of Network Learning Technology, National Central University, TaiwanNarzikul ShadievDepartment of Pedagogics, Samarkand State University, Uzbekistan
2014en
ABI

Abstract

One major drawback of previous research on speech-to-text recognition (STR) is that most of their findings showing an effectiveness of STR for learning in traditional classroom were based on subjective evidences. Very few studies have used eye-tracking techniques to investigate visual attention of students on STR generated text. Furthermore, not much attention was paid to learning differences (i.e. Learning ability) to use STR-text. Therefore, this study carried out one experiment in which participants' visual attention on STR generated text during lectures was investigated by employing eye-tracking technique. Besides, how differently effective STR-text can be to influence participants' learning achievement was tested. Furthermore, this paper discusses results, research findings, and implications along with conclusions and several suggestions for future development and research.

Topics

Identifiers

Citations and references

Cited by 017 references
Metrics — AkademScholar · Coming soon