Learning Analytics and Visualization of Japanese EFL Learners’ Learning Behavior in Speaking Practice
PROCEEDING
Suro Fu, University of Tsukuba, Japan ; Yuichi Ono, Center for Education of Global Communication (CEGLOC), University of Tsukuba, Japan
Society for Information Technology & Teacher Education International Conference, in Austin, TX, United States ISBN 978-1-939797-27-8 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Abstract
The purpose of this study is to develop a system which supports Japanese learners’ speaking practice utilizing Text-to-Speech (TTS) technology and to investigate how they practice with the system on the basis of learning log data. The characteristics of the system are (i) they can choose words, chunks, sentences, or passage which they prefer to practice at any time; and (ii) the system utilizes a common TTS engine which enables learners to access through Internet. The system stored all the log data on participants’ behaviors; every click of words, chunks, sentences, and passages with time stamps. First, this paper demonstrates how the system visualizes each learner’s learning behavior. The seven-week experimental study shows that there are three types of group observed in the analysis regardless of their proficiency levels. In addition, some participants change their learning behavior depending on the materials.
Citation
Fu, S. & Ono, Y. (2017). Learning Analytics and Visualization of Japanese EFL Learners’ Learning Behavior in Speaking Practice. In P. Resta & S. Smith (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 166-172). Austin, TX, United States: Association for the Advancement of Computing in Education (AACE). Retrieved March 28, 2024 from https://www.learntechlib.org/primary/p/177286/.
© 2017 Association for the Advancement of Computing in Education (AACE)
References
View References & Citations Map- Azuma, J. (2010). Impact of TTS technology on foreign language teaching: New horizons of multimedia teaching material development. Ryutsu Kagaku Daigaku Kyoiku Koudoka Suishin Center Kiyou , 6, 1-11.
- Ferguson, R. (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5-6), 304-317.
- Handley, Z., & Hamel, M.J. (2005) Establishing a methodology for benchmarking speech synthesis for computer-assisted language learning (CALL). Language Learning& Technology, vol.9(3) (pp.99-120).
- Hirai, A. & Oki, T. (2011). Comprehensibility and naturalness of Text-to-Speech synthetic materials for EFL listeners. Daigaku Eigokyouiku Gakkaikiyo, vol.(53) (pp.1-17).
- Kastner, M., & Stangl, B. (2013, January). Exploring a Text-to-Speech Feature by describing learning experience, enjoyment, learning styles, and values—A basis for future studies, 2013 46th Hawaii International Conference on System Sciences (HICSS) (pp. 3-12).
- Levy, M. (2009). Technologies in use for second language learning. The Modern Language Journal, 93(s1), 769-782.
- Romero, C., & Ventura, S. (2013). Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 3(1), 12-27.
- Suro, F., & Ono, Y. (2016). Japanese EFL learners' uses of Text-to-Speech technology and their learning behaviors: A pilot study. 2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), (pp. 296-301).
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