Utilizing robot-tutoring approach in oral reading to improve Taiwanese EFL students’ English pronunciation

Abstract

Although the existing research on educational robots has exhibited the assistance for EFL learners’ English skills, the evidence which shows robot-assisted systems’ effect on adult learners’ English read-aloud is still rare. Nevertheless, read-aloud is still treated as a useful approach in English classes for speech pronunciations in particular in Asia. This study aims at the design of a system that uses a robot as a tutor equips automatic speech recognition to diagnose learners’ errors while they are reading aloud the English passages. The learner is able to practice and improve pronunciations via the diagnosis. An experiment designed with a pretest, a posttest, and a delayed posttest was conducted to evaluate the proposed robot-tutoring system. 19 university students in Taiwan enrolled in the experiment, and learned with the system for 90 minutes per round, with a total of 2 rounds of self-learning. The results showed the participants’ accuracy of read-aloud in the delayed posttest was significantly better than those of the pretest and immediate posttest. In addition, when looking into the investigation of the participants’ perceptions of the system, most were impressed by the system, and also agreed the system was a useful and helpful tool to help reading English passages aloud. Therefore, this study provides evidence of the effects of robot-tutoring approach on adults’ English read-aloud in Taiwan.

Keywords:

• Robot-assisted language learning
• educational robot
• English as a foreign language
• English reading aloud

REVIEWING EDITOR:

• Lin Zhong, School of Education, Southern Illinois University Carbondale, USA

SUBJECTS:

• Software Engineering & Systems Development
• Open & Distance Education and eLearning
• Language Teaching & Learning
• Information & Communication Technology (ICT)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was funded by National Science and Technology Council in Taiwan, grant number NSTC 110-2511-H-035-002-MY2 and 112-2410-H-035-015. It was also supported by the Fundamental Research Grant Scheme provided by the Ministry of Higher Education of Malaysia under grant number FRGS/1/2023/ICT03/UTAR/02/1.

Notes on contributors

Zeng-Wei Hong

Zeng-Wei Hong received B.S., M.S., and Ph.D. degrees in computer science from the department of Information Engineering and Computer Science, Feng-Chia University, Taichung, Taiwan. He was an Assistant Professor and Associate Professor in Asia University, Taiwan during August 2007 to July 2015. From August 2015, he was an Assistant Professor in Faculty of Information and Communication Technology, UTAR, Kampar, Malaysia until July 2020. Now he is an associate professor at the Department of Information Engineering and Computer Science, Feng Chia University, Taiwan. His current research interests include e-learning and software engineering.

Ming-Hsiu Michelle Tsai

Ming-Hsiu Michelle Tsai is an assistant professor at the Department of Foreign Languages and Literature, Feng Chia University, Taiwan. She received her MA in Chinese-English Translation and Interpretation from the Middlebury Institute of International Studies at Monterey, California, USA. Her research interests include the theory, teaching and techniques of translation and interpretation, ESP, cross-cultural, and interdisciplinary studies such as with the AI and IT industries. She has also been an accredited translator and conference interpreter for over 25 years, specializing in political, economic, cultural and technical areas.

Chin Soon Ku

Chin Soon Ku received the Ph.D. degrees from Universiti Malaya, Malaysia, in 2019. He is currently an Assistant Professor at the Department of Computer Science, Universiti Tunku Abdul Rahman, Malaysia. His research interests include AI techniques (such as genetic algorithm), computer vision, decision support tools, graphical authentication (authentication, picture-based password, graphical password), machine learning, deep learning, speech processing, natural language processing and unmanned logistics fleets.

Wai Khuen Cheng

Wai-Khuen Cheng received his B.Sc. and Ph.D. degrees from Universiti Sains Malaysia in 2004 and 2009, respectively. He is currently serving as the Assistant Professor and Deputy Dean of the Faculty of Information and Communication Technology (FICT) at Universiti Tunku Abdul Rahman (UTAR), Malaysia. His research interests include cloud computing, multi-agent systems, social network services, Internet of things, personalized recommendation, and financial technology.

Jian-Tan Chen

Jian-Tan Chen received his M.S. degree in computer science from the department of Information Engineering and Computer Science, Feng-Chia University, Taichung, Taiwan. His research interests include e-learning systems, educational robots, and mobile apps development.

Jim-Min Lin

Jim-Min Lin received the BS degree in Engineering Science and the MS and PhD degrees in Electrical Engineering, all from National Cheng Kung University, Tainan, Taiwan, in 1985, 1987, and 1992, respectively. From February 1993 to July 2005, he was an associate professor at the Department of Information Engineering and Computer Science, Feng Chia University, Taichung City, Taiwan. Since August 2005, he has been a title of Full Professor at the same department. Since August 2012, he has been serving as the Director of Main Library. Between November 2008 and October 2011, he served as the Secretary General of the Computer Society of the Republic of China (CSROC). His research interests include Operating Systems, Testable Design, Software Integration/Reuse, Embedded Systems and Software Agent Technology.