Exploring the Possibility of Using a Humanoid Robot as a Tutor and Oral Test Proctor in Chinese as a Foreign Language

Hsuan Li*, Da Yang, Yoshihiro Shiota

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

College students studying foreign languages have the capability to learn vocabulary and grammar and can practice listening, reading, and writing skills by themselves, but they often lack opportunities for speaking and conversation. Robot-assisted language learning (RALL) provides a solution. In this paper, we present an exploratory study on using humanoid robots as tutors to automatically conduct dialogue-based tests with freshman. In the test, students examine pictures, listen to questions asked by the robot, and then say an answer. The test has three parts: answer freely, choose the correct answer by speaking the number, and read the sentence aloud, listen to some options, and choose the best sentence. After each answer, through speech to text (STT) technology, the students’ responses will display on a screen immediately so that the students can ascertain whether their pronunciation or speech output is correct. In this paper, we describe the test design and setup and conduct a preliminary experiment. Finally, we provide an analysis from observations of video data and from students’ comments and discussion. We also identify some necessary improvements for the robot, such as improving its sensitivity to the foreign language learner’s voice.

Original languageEnglish
Title of host publicationLecture Notes in Educational Technology
PublisherSpringer Science and Business Media Deutschland GmbH
Pages113-129
Number of pages17
DOIs
Publication statusPublished - 2021

Publication series

NameLecture Notes in Educational Technology
ISSN (Print)2196-4963
ISSN (Electronic)2196-4971

Keywords

  • Chinese as a Foreign Language (CFL)
  • Educational robot
  • Human–Robot Interaction (HRI)
  • Robot-Assisted Language Learning (RALL)

ASJC Scopus subject areas

  • Education
  • Computer Science Applications
  • Computer Networks and Communications

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