Investigating applications of speech-to-text recognition technology for a face-to-face seminar to assist learning of non-native English-speaking participants

Abstract

2015):Investigating applications of speech-to-text recognition technology for a face-to-face seminar to assist learning of non-native English-speaking participants, Technology, Pedagogy and Education, This study applied speech-to-text recognition (STR) technology to assist non-native English-speaking participants to learn at a seminar given in English. How participants used transcripts generated by the STR technology for learning and their perceptions toward the STR were explored. Three main findings are presented in this study. Most participants perceived that transcripts were useful for learning. Nineteen learning strategies to use transcripts were discovered; transcripts were used to understand the topic presented, to find an answer to a question and to write summaries. Participants with different learning achievements demonstrated different learning behaviours when using transcripts. That is, some participants used transcripts effectively (i.e. studied them thoroughly and used the most important parts of them for summaries along with elaborating ideas) but some participants did not (i.e. studied transcripts superficially and employed the copy-and-paste method to complete summaries). Therefore, this study suggests how to teach participants to use transcripts by employing learning strategies meaningfully.

Evaluating listening and speaking skills in a mobile game-based learning environment with situational contexts

“…For example, gaming contexts are potentially rich venues to deliver language learning (Belz & Reinhardt, 2004), and games provide opportunities for real communication and encourage meaningful interaction and helpful feedback among student participants (Thorne, Black, & Sykes, 2009;Shadiev, Hwang, & Huang, in press). Reinhardt (2014), Shadiev et al (2015), and Thorne et al (2009) argued that educational games bridge the gap between the classroom and the real world. Besides, digital games are highly motivating; thus, they make learning fun and relaxing (Sandberg et al, 2011).…”

“…However, there are limited opportunities to speak English or listen to a speech in English in countries where the native language is not English (Shadiev, Hwang, Huang, & Liu, 2015). According to Cheon (2003), Shadiev et al (2015), and Tsou (2005), some factors that lead to the lack of verbal and aural practice are the absence of an English context, deficiency of good spoken English examples, and excessive dependence upon traditional teaching techniques.…”

Investigating an application of speech‐to‐text recognition: a study on visual attention and learning behaviour

“…Recent evidence suggests that, in physical and online learning environment, some challenges and limitations remain unsolved and thus still need answering (Chen, Ko, Kinshuk, & Lin, ; Shadiev, Hwang, & Huang, ). For example, on an academic event, significant information is usually addressed through audio channels so that students with learning or physical disabilities, foreign students and other populations at risk are challenged to understand the content (Shadiev, Hwang, & Huang, in press). Furthermore, one of the most common concerns reported in relation to online learning literature is the presence of poor audio quality due to restricted bandwidth availability and traffic congestion in the last mile Internet access (Chen et al ., ).…”

“…Furthermore, one of the most common concerns reported in relation to online learning literature is the presence of poor audio quality due to restricted bandwidth availability and traffic congestion in the last mile Internet access (Chen et al ., ). These problems can hinder students' understanding of a delivered speech, and this may hamper students from engaging in classroom participation and interaction (Chen et al ., ; Shadiev et al ., in press).…”

“…According to related literature, the above‐mentioned problems can be solved by adopting speech‐to‐text recognition (STR) technology (Hwang, Shadiev, Kuo, & Chen, ; Kuo, Shadiev, Hwang, & Chen, ; Ryba, McIvor, Shakir, & Paez, ; Shadiev et al ., in press; Speech Recognition in Schools, ). STR technology synchronously transcribes text streams from speech input and shows them on a whiteboard or students' computer screens.…”