IJIET 2025 Vol.15(10): 2058-2071
doi: 10.18178/ijiet.2025.15.10.2405
doi: 10.18178/ijiet.2025.15.10.2405
Revolutionizing Language Learning: The Power of AI-Driven Chatbots in Enhancing Engagement and Proficiency
Hesti Fibriasari1, Bakti Dwi Waluyo2,*, Tansa Trisna Astono Putri2, Tengku Ratna Soraya1,
and Nurilam Harianja1
1. Department of Foreign Languages, Faculty of Languages and Arts, Universitas Negeri Medan, Medan, Indonesia
2. Department of Electronic Engineering Education, Faculty of Engineering, Universitas Negeri Medan, Medan, Indonesia
Email: hesti@unimed.ac.id (H.F.); bakti_dw@unimed.ac.id (B.D.W.); tansatrisna@unimed.ac.id (T.T.A.P.); ratnasoraya@unimed.ac.id (T.R.S.); nurilam@unimed.ac.id (N.H.)
*Corresponding author
2. Department of Electronic Engineering Education, Faculty of Engineering, Universitas Negeri Medan, Medan, Indonesia
Email: hesti@unimed.ac.id (H.F.); bakti_dw@unimed.ac.id (B.D.W.); tansatrisna@unimed.ac.id (T.T.A.P.); ratnasoraya@unimed.ac.id (T.R.S.); nurilam@unimed.ac.id (N.H.)
*Corresponding author
Manuscript received February 14, 2025; revised March 18, 2025; accepted March 28, 2025; published October 14, 2025
Abstract—Integrating Artificial Intelligence (AI) into language learning has substantially enhanced accessibility and engagement by offering interactive and adaptive experiences. However, many AI-driven chatbots lack contextual relevance, limiting their effectiveness for vocational high school students who require career-oriented language instruction. This study aims to develop and evaluate EduNetPro (Education Network for Professional Learning), a multilingual AI-driven chatbot designed to enhance French language learning among vocational students by incorporating adaptive learning pathways, interactive exercises, and gamification elements. Adopting a Design-Based Research (DBR) approach, this study employs a mixed-methods approach, combining quantitative assessments (pre-test and post-test evaluations) with qualitative analyses (student interviews and chatbot interaction logs) to assess EduNetPro’s effectiveness. The findings indicate a 24% improvement in language proficiency, with 80% of students reporting increased engagement and 90% highlighting the efficacy of real-time feedback. Despite these positive outcomes, the chatbot encountered challenges in processing complex dialogues, particularly those involving idiomatic expressions and context-dependent language, emphasizing the need for advancements in Natural Language Processing (NLP) models. This study contributes to the ongoing discourse on AI in education, demonstrating how chatbot-driven learning can address the unique needs of vocational students by providing contextualized, career-focused language instruction. Future research should further explore AI-driven emotional intelligence, enhanced personalization strategies, and long-term language retention to optimize AI-assisted learning environments.
Keywords—Artificial Intelligence (AI)-driven chatbots, natural language processing, vocational education, student engagement, adaptive learning
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—Artificial Intelligence (AI)-driven chatbots, natural language processing, vocational education, student engagement, adaptive learning
Cite: Hesti Fibriasari, Bakti Dwi Waluyo, Tansa Trisna Astono Putri, Tengku Ratna Soraya, and Nurilam Harianja, "Revolutionizing Language Learning: The Power of AI-Driven Chatbots in Enhancing Engagement and Proficiency," International Journal of Information and Education Technology, vol. 15, no. 10, pp. 2058-2071, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).