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Investigating an application of speech‐to‐text recognition: a study on visual attention and learning behaviour
Author(s) -
Huang YM.,
Liu CJ.,
Shadiev R.,
Shen MH.,
Hwang WY.
Publication year - 2015
Publication title -
journal of computer assisted learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.583
H-Index - 93
eISSN - 1365-2729
pISSN - 0266-4909
DOI - 10.1111/jcal.12093
Subject(s) - eye tracking , psychology , visual learning , style (visual arts) , cognitive psychology , perception , visual attention , learning styles , computer science , artificial intelligence , developmental psychology , archaeology , neuroscience , history
One major drawback of previous research on speech‐to‐text recognition ( STR ) is that most findings showing the effectiveness of STR for learning were based upon subjective evidence. 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, such as learning ability, learning style preferences and gender, to use STR texts. Therefore, this study carried out one experiment. Firstly, participants' visual attention on STR ‐generated text was investigated by employing eye‐tracking technique. Secondly, how differently effective STR ‐generated texts can be to influence participants' learning achievement was tested. Thirdly, this study compared visual attention and learning behaviour with the different characteristics of participants, such as learning ability, learning style preferences and gender, to use STR ‐generated texts. Finally, this study explored students' perceptions regarding usefulness of STR ‐generated texts for learning. This paper discusses results, research findings and implications along with conclusions and several suggestions for future development and research.