Teaching University English in the AI Age: A Learning Model That Cuts Time, Increases Results, and Accelerates Skill Development
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Abstract
The Artificial Intelligence (AI) revolution, particularly the advent of Large Language Models (LLMs), has driven a significant structural transition in English language teaching within higher education. This article aims to analyze AI concepts, theories, and technologies relevant to modern English language instruction and proposes a systemic framework for Thai universities through the “AI-Accelerated ELT Framework.” This model integrates Communicative Language Teaching (CLT), Task-Based Language Teaching (TBLT), Flipped Classroom, and Self-Regulated Learning (SRL) with technologies such as Natural Language Processing (NLP), Intelligent Tutoring Systems (ITS), Automated Writing Evaluation (AWE), and Generative AI.
A review of the literature indicates that AI can support personalized learning, automated content adaptation, and real-time feedback, enabling learners to develop language fluency more rapidly and significantly reducing the burdens of traditional learning. However, the use of AI still faces limitations regarding data accuracy (hallucinations), data privacy, and the risks of over-reliance. Consequently, this article proposes ethical and “human-in-the-loop” approaches to AI utilization, alongside policy recommendations for AI literacy for both instructors and learners, to ensure that AI applications in Thai universities are maximized and sustainable.
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- ต้นฉบับที่ได้รับการตีพิมพ์ในวารสารวิชาการ มหาวิทยาลัยราชภัฏบุรีรัมย์ สาขามนุษยศาสตร์และสังคมศาสตร์ ถือเป็นกรรมสิทธิ์ของมหาวิทยาลัยราชภัฏบุรีรัมย์ ห้ามนำข้อความทั้งหมดหรือบางส่วนไปพิมพ์ซ้ำเว้นเสียแต่ว่าจะได้รับอนุญาตจากมหาวิทยาลัยฯ เป็นลายลักษณ์อักษร
- เนื้อหาต้นฉบับที่ปรากฏในวารสารเป็นความรับผิดชอบของผู้เขียน ทั้งนี้ไม่รวมความผิดพลาด อันเกิดจากเทคนิคการพิมพ์
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