Speakers
Description
This study addresses a critical gap in the integration of Artificial Intelligence (AI) within instructional design for English for Specific Academic Purposes (ESAP), an area often overlooked in AI-assisted language education research. While much of the existing work focuses on general English instruction or AI-driven assessment tools, little has explored how AI can support task-based, motivationally grounded ESAP learning that promotes global readiness and sustainability. Grounded in Deci and Ryan’s Self-Determination Theory (1985, 2000), this research also fills a theoretical gap by linking AI-enhanced instruction with learner autonomy, competence, and relatedness. Using a quantitative approach, data were collected through structured questionnaires from 256 students across 25 ESAP classes (from a population of 1,000). Findings show that 73% of students believed the AI-supported instructional design met their academic and real-world needs, while 69% felt more motivated and 65% pursued independent research beyond the materials. However, 23% felt unsure of its relevance, and 30% remained hesitant to go beyond the given content. These results affirm the promise of AI-enhanced ESAP design in supporting student motivation and global preparedness, while also highlighting areas for pedagogical improvement.
Keywords: AI in ESAP, Instructional Design, Self-Determination Theory
Biography
Emanuella Christine Natalia Mau, M.Hum, CIQaR is a lecturer at Universitas Multimedia Nusantara in Tangerang, Jakarta, with academic roots in English language education, creative writing, and film criticism. Her professional work focuses on developing innovative curricula that merge language education with interdisciplinary content, emphasizing learner autonomy, academic literacy, and the ethical use of artificial intelligence in classroom instruction. She is particularly engaged in the design and implementation of English for Specific Academic Purposes (ESAP) programs tailored to vocational and academic disciplines. Emanuella has presented her research and pedagogical innovations at major conferences, including ASIATEFL and TEFLIN, where she showcased strategies for integrating AI tools in language education and explored the impact of task-based instruction on student agency. With her background in narrative and critical analysis, she brings a humanistic and reflective approach to language teaching, making her a strong advocate for student-centered and culturally responsive learning environments in Indonesian higher education.
