A Task-Based Role-Playing Game with Educational Robots for Learning Language

Chen, Gwo-Dong; Chang, Chia Ju

doi:10.1007/978-3-642-03364-3_58

Cited by 3 publications

(1 citation statement)

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“…Task-based language teaching (TBLT) is based on CLT, but concentrates on having learners complete explicit tasks [28]. Both CLT and TBLT are quite popular in RALL, especially in research coming from Asia (e.g., References [22,66,114]). They were established in response to an older technique, which is still used, called the audiolingual method (ALM).…”

Section: Instructional Methodsmentioning

confidence: 99%

A Survey of Robot-Assisted Language Learning (RALL)

Randall

2019

J. Hum.-Robot Interact.

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Robot-assisted language learning (RALL) is becoming a more commonly studied area of human-robot interaction (HRI). This research draws on theories and methods from many different fields, with researchers utilizing different instructional methods, robots, and populations to evaluate the effectiveness of RALL. This survey details the characteristics of robots used-form, voice, immediacy, non-verbal cues, and personalizationalong with study implementations, discussing research findings. It also analyzes robot effectiveness. While research clearly shows that robots can support native and foreign language acquisition, it has been unclear what benefits robots provide over computer-assisted language learning. This survey examines the results of relevant studies from 2004 (RALL's inception) to 2017. Results suggest that robots may be uniquely suited to aid in language production, with apparent benefits in comparison to other technology. As well, research consistently indicates that robots provide unique advantages in increasing learning motivation and in-task engagement, and decreasing anxiety, though long-term benefits are uncertain. Throughout this survey, future areas of exploration are suggested, with the hope that answers to these questions will allow for more robust design and implementation guidelines in RALL.

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Section: Instructional Methodsmentioning

confidence: 99%