Comparative analysis evaluates homework's effectiveness in AI-driven learning environments, suggesting new instructional approaches.
This study examines the emerging crisis surrounding traditional homework, particularly its diminishing pedagogical effectiveness in the context of the rapid integration of artificial intelligence (AI) into contemporary educational environments. It further explores how the “Flipped Classroom” model may serve as a viable alternative for restructuring instructional practices and enhancing student engagement. The relevance of this issue lies in the growing evidence that AI tools are reshaping students’ learning behaviors by reducing motivation for independent cognitive effort, thereby challenging established principles of academic integrity, responsibility, and formative assessment. Methodologically, the study adopts a comparative analytical approach to evaluate the pedagogical efficiency of AI-assisted learning environments in contrast with traditional homework-based instruction. Special attention is given to the ways in which in-class engagement can be reorganized to promote deeper cognitive involvement, critical thinking, and active participation. The analysis draws on recent educational research and instructional design perspectives that emphasize process-oriented learning over product-oriented assessment. The findings suggest that unregulated reliance on AI in out-of-class assignments undermines the developmental purpose of homework as a learning tool. Therefore, rather than maintaining traditional homework practices in their current form, the study argues for a fundamental pedagogical shift. In this regard, it proposes either the elimination of conventional homework or its transformation into a fully classroom-integrated learning process, where guided instruction, collaborative practice, and real-time feedback replace independent, AI-mediated completion.
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İBRAHİMOV et al. (2026) studied this question.
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