Journal of AI in ELT and Applied Linguistics was first published in 2025 and is regularly published twice per year.

Journal Title	: Journal of AI in ELT and Applied Linguistics (JAIELA)
Initial	: JAIELA
Abbreviation	: XXXX-XXXX
ISSN	: 2X (media online)
DOI Prefix	10.58723 by
Publisher	: CV Media Inti Teknologi
insitution and Assosiation	: -
Editor in Chief	: Dr. Imam santosa (Scopus ID: 59201706100)
Journal Rank	: Progress
Frequency	: 2 issues per year: June, December
Focus & Scope	: 1. Artificial Inteligence   2. ELT   3.Applied Linguistics
OAI Addres s	https://e-journal.gomit.id/index.php/jaiela/oai
Submission	: This journal welcomes submissions all year round. Submissions are reviewed upon receipt. The template manuscript can be downloaded [Here]. Manuscript Published is written in standard English since Volume 1 Number 1, 2025.

Abstracted/Indexed by:

 

   

The journal welcomes rigorous contributions covering a wide spectrum of topics where AI meets ELT. Areas of interest include, but are not limited to:

AI-Powered Learning Systems: Design, development, implementation, and evaluation of AI-driven tools for English language learning (e.g., intelligent tutoring systems (ITS), chatbots for conversational practice, adaptive learning platforms, AI-enhanced virtual/augmented reality environments).
Natural Language Processing (NLP) for ELT: Application of NLP techniques for ELT purposes, such as automated writing evaluation (AWE), grammatical error detection and correction, text simplification, plagiarism detection, sentiment analysis of learner language, and corpus analysis using AI.
Machine Learning in ELT: Use of machine learning models for personalizing learning pathways, analyzing learner data and behavior, predicting learner outcomes, developing diagnostic assessments, and understanding language acquisition processes.
AI in Language Assessment: Research on AI-based tools for formative and summative assessment of English language skills (speaking, writing, reading, listening), including automated scoring, item generation, and adaptive testing.
Speech Technology for ELT: Application of automatic speech recognition (ASR) and text-to-speech (TTS) synthesis for pronunciation training, fluency development, and spoken interaction practice.
Data Analytics and AI Ethics in ELT: Exploration of learning analytics powered by AI to understand learner engagement and progress; critical studies on ethical considerations, including data privacy, algorithmic bias, fairness, transparency, teacher roles, and the digital divide in AI-driven ELT.
Human-Computer Interaction (HCI): Studies focusing on the usability, user experience, and pedagogical effectiveness of interactions between learners/teachers and AI-based ELT systems.
AI for Specific ELT Contexts: Research on AI applications tailored for specific needs, such as English for Specific Purposes (ESP), English for Academic Purposes (EAP), young language learners, learners with disabilities, and diverse multilingual settings.
Teacher Education & AI Literacy: Investigations into preparing ELT educators to effectively understand, utilize, critique, and integrate AI tools into their teaching practices.
Theoretical & Conceptual Contributions: Papers exploring theoretical frameworks that integrate AI concepts with theories of Second Language Acquisition (SLA) and ELT methodologies.
Applied Linguistics