Designing an LLM-based IELTS question generator, assessment, and personalized training system: architecture and research agenda

Name: Thanayut Tiratatri

Organization : Chulalongkorn University. International School of Engineering, Faculty of Engineering

Email : 6438097921@student.chula.ac.th

Name: Kanin Sukittivarapunt

Organization : Chulalongkorn University. International School of Engineering, Faculty of Engineering

Email : 6438024021@student.chula.ac.th

Name: Pyae, Aung

Organization : Chulalongkorn University. International School of Engineering, Faculty of Engineering

Email : aung.p@chula.ac.th

Name: Thammathat Sarasinpitak

Organization : Chulalongkorn University. International School of Engineering, Faculty of Engineering

Email : 6438101721@student.chula.ac.th

keyword: Large language models

LCSH: English language -- Examinations -- Study guides

LCSH: Intelligent tutoring systems -- Design and construction

LCSH: Language and languages -- Ability testing -- Automation

LCSH: Artificial intelligence

Abstract: While generative AI tools like LLMs have begun to assist in IELTS preparation, most fail to provide skill-specific, exam-aligned feedback across all four sections: Listening, Reading, Writing, and Speaking. This paper introduces NOAH, a novel LLM-based preparation system designed using a structured SDLC and LLMOps framework. Unlike generic AI tutors, NOAH features custom fine-tuned GPT-4o models trained on authentic IELTS materials, prompt-chained question generation, and automated visual and audio synthesis for realistic task simulation. The system supports modular skill pipelines, adaptive mock testing, and speech-based scoring using Azure APIs, delivering a full-stack solution optimized for personalization, scalability, and accessibility. Guided by human-centered AI principles, NOAH bridges pedagogical precision with generative AI flexibility, setting a foundation for equitable and high-fidelity language assessment preparation

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2025

Modified: 2026-06-10

Issued: 2026-06-10

บทความ/Article

application/pdf

BibliograpyCitation : In Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI) Association, Thailand. 2025 22nd International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2025) (pp.116-121). Piscataway, NJ : IEEE

eng

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