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p-Index From 2021 - 2026
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All Journal International Journal Artificial Intelligent and Informatics Innovations in Language Education and Literature
John Bunce
California State University
Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media

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Exploring Early Childhood Linguistic Intelligence Through English Language Learning Methods Gumarpi Rahis Pasaribu; Rani Arfianty; John Bunce
Innovations in Language Education and Literature Vol. 1 No. 2 (2024): DECEMBER 2024
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/ilere.v1i2.4337

Abstract

This study investigates the effectiveness of interactive learning methods; playing, singing, and storytelling in enhancing linguistic intelligence among early childhood learners in English language settings. Adopting a qualitative case study approach, data were collected through classroom observations, semi-structured interviews with teachers and parents, and field notes. The findings reveal that interactive methods significantly improve children's engagement, vocabulary acquisition, and ability to construct simple sentences. Activities such as singing and storytelling not only boost verbal responses but also build children's confidence in using English both in and outside the classroom. Parents observed enhanced communication skills and self-confidence at home. Additionally, these methods contributed to cognitive development, fostering critical thinking and creativity. The study concludes that interactive English learning activities are instrumental in fostering linguistic intelligence in early childhood while providing a strong foundation for future academic and communication skills. Recommendations for integrating these methods into preschool curricula are provided, highlighting their potential for global adaptation in early language education.
The Role of Artificial Intelligence in Enhancing Foreign Language Learning: Toward Guided Human–AI Language Learning (GHAILL) John Bunce; Gumarpi Rahis Pasaribu; Nanda Dwi Astri; Nurainun Hasibuan; Dara Mubshirah
International Journal Artificial Intelligent and Informatics Vol. 4 No. 3 (2026): August 2026
Publisher : Research and Social Study Institute (ReSSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/0sdyya49

Abstract

  Artificial intelligence (AI) is rapidly reshaping foreign language learning by providing learners with immediate linguistic support, conversational practice, adaptive feedback, and opportunities for learning beyond formal classroom time. Yet the pedagogical value of AI cannot be reduced to technological availability alone. This qualitative study is designed to explore how 30 university students experience AI-supported foreign language learning, with particular attention to speaking development, learner agency, engagement, feedback, confidence, self-regulated learning, and critical AI literacy. Data are to be collected through semi-structured interviews and, where available, supplementary learning reflections or AI interaction records. The study adopts reflexive thematic analysis to identify patterns in how students use AI to rehearse speech, generate ideas, expand vocabulary, check grammar, seek pronunciation support, manage speaking anxiety, and regulate independent learning. At the same time, the study examines tensions related to inaccurate output, dependency, superficial learning, privacy, academic integrity, and the limited authenticity of machine-mediated interaction. The manuscript proposes Guided Human-AI Language Learning (GHAILL) as an interpretive model in which learners move from goal setting to AI-mediated practice, critical evaluation, linguistic modification, human communication, and reflection. The central argument is that AI is most educationally valuable when it functions as a scaffold and rehearsal partner rather than a substitute for learner thinking, teacher guidance, or human interaction. The study contributes to emerging scholarship on generative AI in language education by connecting AI use with agency, self-regulation, willingness to communicate, and speaking development in a university context.
Co-Authors Dara Mubshirah Gumarpi Rahis Pasaribu Nanda Dwi Astri Nurainun Hasibuan Rani Arfianty