The affordance of speech recognition technology for EFL learning in an elementary school setting

Abstract

This study examined the use of speech recognition (SR) technology to support a group of elementary school children's learning of English as a foreign language (EFL). SR technology has been used in various language learning contexts. Its application to EFL teaching and learning is still relatively recent, but a solid understanding of its effectiveness for EFL learning is important because SR-based programs are now available online and easily accessible to many EFL learners worldwide. In this study, an online reading program featuring SR technology has been used as supplementary materials for a group of EFL elementary school students to maintain their interest as well as to advance in English learning. The researcher examined and analyzed the students' performance from the tracking system. Field observations and interviews with both children and the EFL teacher were also conducted to understand how they responded to the feedback provided by the program and their perceived affordance of SR technology for their learning.

Keywords:

• speech recognition technology
• EFL
• elementary school
• Reading Companion
• technology affordance

Notes on contributor

Meei-Ling Liaw is a professor in the Department of English at National Taichung University. Her research focuses on using computer technology to facilitate EFL teaching and learning, intercultural learning, and teacher education. Her publications have appeared in professional journals including System, Foreign Language Annals, Computer-Assisted Language Learning, ReCALL, and Language Learning and Technology. She has been serving on the editorial board of Language Learning and Technology since 2008.

Notes

1. Project LISTEN (http://www.cs.cmu.edu/~listen/) was founded in early 1990s. It used the computer as a tutor to teach vocabulary to children (Mostow and Aist 2001). The sentences were presented on the screen one at a time, and assistance took the form of pictorial clues, rhyming words, sounding out, and spelling to help with words that were identified by the system as likely to be difficult, based on word length. When to use what type of assistance was randomly determined by the system.

2. At the time of the project, there were 85 e-books for children in grades kindergarten to second (aged 5–7) grades. For adults, there were approximately 157 e-books on topics ranging from job search and employment, driving, US citizenship, housing, financial issues, and other topics relevant to the lives of adult learners.

3. The tracking system records the following reading behaviors: words attempted, words correct, words incorrect, word accuracy, rules/word-features encountered, correct rules/features, incorrect rule/feature, and rules/features accuracy.

4. Kartal (2006) identified four types of metacognitive patterns of interaction and two types of word level interaction patterns between learners and SR technology. The metacognitive patterns include self-correction/change, repetition, metalinguistic comments, and extra practice. The word level interaction patterns are (1) adding or deleting a morpheme and (2) reading a similar word.

5. ‘c’ at the end of a syllable sounds like ‘k’, c followed by ‘o’ sounds like ‘k’, ‘c’ followed by ‘a’ sounds like ‘k’, ‘c’ followed by ‘y’ sounds like ‘s’, c followed by ‘i’ sounds like ‘s’, and ‘c’ followed by ‘e’ sounds like ‘s’.

6. Silent-e rule makes long ‘e’, ‘silent-e rule’ makes long ‘I’, ‘silent-e rule’ makes long ‘o’, ‘silent-e rule’ makes long ‘a’, and silent-e rule makes long ‘u’.

7. Consonant blends ‘cl’, ‘bl’, ‘pl’ ‘fr’, ‘gr’, and ‘st’ and consonant blends ‘rd’, ‘ld’, ‘ll’, ‘nd’, ‘rn’, ‘wn’, ‘rl’, ‘rst’, ‘ch’, and ‘pp’ are closing syllables.