Eri Yamashita

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Senior at Chuo University | Majoring in global informatics

Sessions

Computer Assisted Language Learning Effects of AI Speaking Application on Students’ Speaking and Listening more

Sat, Jul 9, 14:05-14:30 Asia/Tokyo

The emergence of COVID-19 has promoted the wide use of Artificial Intelligence(AI) educational digital tools (Almarzooq et al., 2020), and one example of AI educational digital tools is the automatic scoring application that provides feedback on pronunciation (Fu et al., 2020). Ahn and Lee (2016) found that automatic speech recognition enhances language learning regarding pronunciation and speaking. Improving pronunciation may help English learners improve their listening comprehension. Understanding rules of phonemes and pronunciation is one of the top-down approaches to listening(Flowerdew&Miller, 2005). In order to investigate the effects of one AI application to practice pronunciation and speaking, ELSA Speak, eight university students took training of pronunciation focusing on improvements of phonemes using the application for about 40 days. Before and after the training, they took pre-and post- speaking tests and pre-and post- listening tests. To support students’ ongoing learning, the presenters had students self-and peer-evaluate weekly on an application for mobile phones, LINE, as a part of a cyclical phase of Self-Regulated Learning (Zimmerman, 2010). The results of the post-TOEIC listening test showed that the seven students improved their listening scores though only two students showed improvements on the post-speaking test. The presenters will also discuss whether the self-and peer- evaluation on LINE was helpful for the students to continue studying with the application.

Yukie Saito Eri Yamashita