Article Gold Open Access 2022

Autonomous Learning Through Chatbot-based Application Utilization to Enhance Basic Japanese Competence of Vocational High School Students

Journal of Technical Education and Training
Journal · Vol. 14 · Issue 2 SPECIAL ISSUE · pp. 143-155
Abstract

This study sought to examine vocational students’ evaluation and feedback regarding the chatbot-based application as an assistive technology in learning basic Japanese in vocational high school and investigate students’ recommendations on the possible future advancement of the chatbot-based application to help students learn the Japanese language better. This study employed a questionnaire and follow-up interview to collect the data, which questionnaire was administered to 100 vocational students enrolled in 8 state vocational high schools located in different regions in Indonesia. The data collected were analysed using SPSS 24, and also tested for reliability and validity. The findings of this study denote the use of the chatbot-based application, namely Gengobot, useful in enhancing students’ basic Japanese grammar learning, improving vocabulary mastery related to vocational terminologies, providing practices for basic Japanese language level exercise, having attractive and interactive features, and fostering learners’ autonomy and independence learning due to its practicality, portability, accessibility, and flexibility. The results also conveyed the practicality problems and confusion in using the application as an application integrated into social media. Hence, further development of the chatbot-based application Gengobot as assistive technology in learning Japanese is recommended. All in all, the chatbot-based application Gengobot as an assistive Japanese language learning application can be concluded as compelling, and is recommended to be used for vocational students to enhance autonomous learning as well as to support distance learning. © Universiti Tun Hussein Onn Malaysia Publisher’s Office.

Keywords

Author Keywords

Vocational education language learning social media chatbot Autonomous learning Gengobot Japanese

Index Keywords

Author Affiliations
Universitas Pendidikan Indonesia, Bandung, West Java, Indonesia
Funding & Acknowledgements
Kementerian Riset Teknologi Dan Pendidikan Tinggi Republik Indonesia
We express our gratitude and acknowledge the Directorate of Research and Community Service, Ministry of Research, Technology and Higher Education, the Republic of Indonesia for the financial support for this research through the grant of Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT) fiscal year of 2022.
Direktorat Riset dan Pengabdian Masyarakat, DRPM
We express our gratitude and acknowledge the Directorate of Research and Community Service, Ministry of Research, Technology and Higher Education, the Republic of Indonesia for the financial support for this research through the grant of Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT) fiscal year of 2022.
References 10 References
1 International Journal of Advanced Computer Science and Applications, (2015)
2 Klik Kumpulan Jurnal Ilmu Komputer, (2025)
3 Balçikanli, Cem, Learner autonomy in language learning: Student teachers' beliefs, Australian Journal of Teacher Education, 35, 1, pp. 90-103, (2010)
4 Baudart, Guillaume, Reactive chatbot programming, REBLS 2018 - Proceedings of the 5th ACM SIGPLAN International Workshop on Reactive and Event-Based Languages and Systems, Co-located with SPLASH 2018, pp. 21-30, (2018)
5 Educational Research, (2013)
6 Chapelle, Carol A., Computer‐Assisted Language Learning as a Predictor of Success in Acquiring English as a Second Language, TESOL Quarterly, 20, 1, pp. 27-46, (1986)
7 Language Learning Technology, (2006)
8 Decoo, Wilfried, In defence of drill and practice in CALL: A reevaluation of fundamental strategies, Computers and Education, 23, 1-2, pp. 151-158, (1994)
9 Dickinson, Leslie, Autonomy and motivation a literature review, System, 23, 2, pp. 165-174, (1995)
10 Fryer, Luke K., Bots as language learning tools, Language Learning and Technology, 10, 3, pp. 8-14, (2006)
Quick Actions
Full Text via DOI
Citation Metrics
12
Times Cited (Scopus)

References 10
Document Identifiers