Yan.Deng
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Presentation Exploring AI-Generated Materials for ESAP in STEM: A CALL-Based Evaluation of Engagement, Efficiency, and Adaptability at XJTLU more
As AI tools become increasingly integrated into language education, their role in Computer-Assisted Language Learning (CALL) requires critical examination. This study, conducted at Xi'an Jiaotong-Liverpool University (XJTLU), a flagship Sino-British institution in China, explores the use of AI-assisted materials in teaching a Year 2 English for Specific Academic Purposes (ESAP) module for STEM students in a transnational context. Through a CALL-oriented framework, the research investigates how AI-generated materials impact student engagement, lesson planning, and additional exercises. By evaluating the efficiency, content quality, and adaptability of AI-generated learning resources, this study assesses their alignment with discipline-specific language use, students' proficiency levels, and pedagogical best practices in CALL. Additionally, the research addresses key challenges such as the authenticity of AI-generated content, the role of instructor mediation, and the AI literacy required for effective integration. The findings contribute to discussions on optimizing AI tools for CALL-based language instruction, offering practical insights into their application in STEM-focused curricula and beyond.
Poster Session Leveraging AI Tools to Develop Teaching Materials for an ESAP Module in Engineering Education more
This study investigates the integration of AI tools in developing teaching materials for an English for Specific Academic Purposes (ESAP) module tailored for Engineering students at Xi’an Jiaotong Liverpool University, a Sino-British institution and EMI university. The module enrolls approximately 600 students, with around 120 directly taught by the presenter in groups of about 20 each. The focus is on utilizing AI technologies—such as ChatGPT or DeepSeek—and voice tools like MURF AI to design reading and listening exercises that meet the specific needs of students specializing in fields such as big data and microelectronics. Students are expected to achieve a B2+ level on the Common European Framework of Reference (CEFR) after one year of study. The poster will demonstrate the process of incorporating advanced AI technology into lesson planning by presenting a detailed example of a complete lesson plan that illustrates the development of effective prompts and the generation of materials aligned with targeted learning outcomes and discipline-relevant topics. Employing a reflective approach, this study provides insights into the potential of AI in language teaching for specialized disciplines and offers a teacher’s perspective on the practical applications and challenges of integrating AI in the classroom.