Beyond Curriculum Adoption: Generative Artificial Intelligence (GenAI), Puzzle-Based Instruction, and EFL Teachers’ Pathways to Curriculum Innovation

The increasing complexity of language education has challenged traditional views of curriculum implementation and materials use in English as a Foreign Language (EFL) contexts. While published materials remain the primary instructional resource for many teachers, contemporary curriculum theory suggests that effective teaching extends beyond the mere adoption of prescribed content. This conceptual paper critically examines three major curriculum orientations—curriculum fidelity, adaptation, and enactment—and explores how EFL teachers negotiate the selection, modification, and development of instructional materials. Drawing on literature in curriculum studies, materials development, and language pedagogy, the paper positions Puzzle-Based Instruction (PBI) as a pedagogical framework that supports teachers in transforming curriculum from static content into dynamic, learner-centered learning experiences. Through processes of deconstruction, adaptation, recombination, and instructional redesign, PBI enhances teacher agency, learner engagement, personalization, and meaningful communication. The paper further argues that emerging technologies, particularly Generative Artificial Intelligence (GenAI), expand opportunities for curriculum innovation by enabling teachers to generate context-sensitive materials, communicative tasks, and adaptive learning activities. Rather than replacing teacher expertise, GenAI functions as a pedagogical partner that supports curriculum enactment and creative instructional design. The paper concludes that the integration of PBI and GenAI provides a promising pathway through which EFL teachers can move beyond curriculum adoption and adaptation toward sustainable curriculum innovation.