Designing Ai-Integrated Teaching Materials For Pre-Service English Teachers: A Lesson From Teachers Professional Education Practices
Authors
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Isry Laila Syathroh
IKIP Siliwangi
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Siti Kustini
Politeknik Negeri Banjarmasin
DOI:
https://doi.org/10.36312/jolls.v6i3.5160Keywords:
Artificial intelligence, Teaching materials, Lesson planning, Teacher educationAbstract
Lesson planning is a core professional skill for pre-service teachers, particularly within Indonesia’s Kurikulum Merdeka, which emphasizes the development of Modul Ajar as flexible, creative, and learner-centered teaching modules. With the growing presence of Artificial Intelligence (AI) in education, this study investigates how pre-service English teachers integrate AI tools into Modul Ajar development, exploring their perceived benefits, challenges, and professional implications. Employing a qualitative descriptive design, data were collected from seven pre-service teachers enrolled in the Pendidikan Profesi Guru (PPG) program through lesson plan documents, reflection journals, and focus group discussions. Thematic analysis was used to examine patterns of AI use, perceptions, and reflections across data sources. Findings reveal that participants used a range of AI tools, such as ChatGPT, Grammarly, Quillbot, and Canva, to support lesson planning. These tools assisted in drafting objectives, generating activities, refining language, and creating visual materials, enabling participants to focus on higher-order pedagogical considerations. Reported benefits included efficiency, improved clarity, enhanced creativity, and support for differentiated instruction. However, participants also identified significant challenges, including over-reliance on AI outputs, contextual misalignment with the Indonesian curriculum, occasional inaccuracies, and the irreplaceable need for human judgment in adapting lessons to learners’ needs. The study underscores that while AI can serve as both a scaffold and a catalyst for reflective practice, its effective integration requires critical evaluation, pedagogical guidelines, and professional judgment. Recommendations highlight the need for AI literacy training, context-sensitive frameworks, and further research on the long-term impact of AI integration on teaching competence and student outcomes.
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