Volume 16, Issue 2 August 2020, pp. 107–120 Download PDF

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Intelligent personal assistants for autonomous second language learning: An investigation of Alexa

Gilbert Dizon https://orcid.org/0000-0001-8906-20291, & Daniel Tang https://orcid.org/0000-0002-6822-30112

1 Himeji Dokkyo University, JAPAN gilbert.dizon.jr@gmail.com
2 Otemae University, JAPAN dtang@otemae.ac.jp

DOI: https://doi.org/10.29140/jaltcall.v16n2.273


Abstract

The ubiquity of smartphones and the growing popularity of smart speakers have given rise to cloud-based, intelligent personal assistants (IPAs), such as Siri and Google Assistant. However, little is known about the use of IPAs for Autonomous Second Language Learning (ASLL). Thus, the aims of this study were twofold: to assess Japanese English as a Foreign Language (EFL) students’ perceptions towards IPAs, also known as virtual assistants, for ASLL, and to better understand learner behavior of these technologies. A total of 14 Japanese university students were given smart speakers and interacted with a companion IPA, Amazon Alexa, over a two-month period in their homes. Moreover, the participants completed a survey consisting of Likert-scale items and open-ended questions to obtain their views of the IPA for ASLL. While the results indicated that the students had mostly favorable views of Alexa for L2 learning, many of them did not actively engage with the virtual assistant during the data collection period. Furthermore, students tended to give up when faced with communication difficulties with the IPA. These findings highlight the potential of IPAs for ASLL and underscore the gap between what students say, and what they actually do, with language learning technology.



Copyright

© Gilbert Dizon, Daniel Tang

CC  4.0
This work is licensed under a Creative Commons Attribution 4.0 International License.


Suggested citation

Dizon, G., & Tang, D. (2020). Intelligent personal assistants for autonomous second language learning: An investigation of Alexa. The JALT CALL Journal, 16(2), 107–120. https://doi.org/10.29140/jaltcall.v16n2.273


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