Robot-Assisted Instruction of L2 Pragmatics: Effects on Young EFL Learners’ Speech Act Performance

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2020-06-01

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University of Hawaii National Foreign Language Resource Center
Center for Language & Technology
(co-sponsored by Center for Open Educational Resources and Language Learning, University of Texas at Austin)

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24

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2

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86

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103

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Abstract

Technology, as a source of instruction, has fulfilled various purposes in foreign language learning environments. During the last decade, Robot-Assisted Language Learning (RALL) has attracted teachers’ and researchers’ attention due to the look and feel of humanoid robots. However, in the field of pragmatics, studies highlighting the role of RALL have gone relatively unnoticed. To bridge this gap, this study sought to explore the effect of RALL on pragmatic features, including request and thanking speech acts by young Persian-speaking EFL learners. For this aim, 38 preschool children (3 to 6 year-old boys and girls) with no English learning experience were randomly assigned to the RALL (19 students) and non-RALL (19 students) groups. In the RALL group, a humanoid robot was used as an assistant to the teacher to play games, repeat the sentences, and interact with the students. In the non-RALL group the lessons included games similar to those in the RALL group, but without the presence of the robot. There were eight one-hour teaching sessions over a period of four weeks for both groups. Following completion of the lessons in both groups, the results of post-tests were analyzed using an independent sample t-test. The findings revealed a significant difference between the RALL and non-RALL groups’ pragmatic performance for thanking and requesting. Based on these findings it can be concluded that RALL instruction was more effective than non-RALL instruction in improving the young learners’ performance.

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RALL, Humanoid robot, Pragmatics instruction, young EFL learners

Citation

Alemi, M., & Haeri, N. S. (2020). Robot-Assisted Instruction of L2 Pragmatics: Effects on Young EFL Learners’ Speech Act Performance. Language Learning & Technology, 24(2), 86–103. http://hdl.handle.net/10125/44727

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