Investigating visual attention of students with different learning ability on texts generated by speech-to-text recognition

Rustam Shadiev, Yueh-Min Huang, Wu Yuin Hwang, Narzikul Shadiev

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014
EditorsRonghuai Huang, Kinshuk, Demetrios G. Sampson, Michael J. Spector, Nian-Shing Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages423-425
Number of pages3
ISBN (Electronic)9781479940387
DOIs
Publication statusPublished - 2014 Sep 17
Event14th IEEE International Conference on Advanced Learning Technologies, ICALT 2014 - Athens, Greece
Duration: 2014 Jul 72014 Jul 9

Publication series

NameProceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014

Other

Other14th IEEE International Conference on Advanced Learning Technologies, ICALT 2014
CountryGreece
CityAthens
Period14-07-0714-07-09

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Education

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    Shadiev, R., Huang, Y-M., Hwang, W. Y., & Shadiev, N. (2014). Investigating visual attention of students with different learning ability on texts generated by speech-to-text recognition. In R. Huang, Kinshuk, D. G. Sampson, M. J. Spector, & N-S. Chen (Eds.), Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014 (pp. 423-425). [6901501] (Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICALT.2014.127