Beyond Task Completion: Enhancing Homework Practices Through AI and Digital Learning Platforms

Introduction. The integration of artificial intelligence (AI) and digital learning platforms is transforming homework practices, raising questions about the relationship between task completion and meaningful learning. The study examines how AI-supported homework can promote cognitive engagement, independent reasoning, and student intellectual responsibility. It introduces the AI-Supported Productive Homework Framework (ASPH), grounded in five principles: purposeful instructional design, active cognitive engagement, guided AI integration, student intellectual responsibility, and process-oriented assessment. Materials and Methods. A quasi-experimental mixed-methods design involving 100 undergraduate students was employed to examine the framework's pedagogical effectiveness. Results. The descriptive comparison indicates a greater improvement in academic performance in the ASPH group. However, inferential analysis of the observed data is required to establish the statistical significance of the difference and assess the intervention's effectiveness. Conclusions. The proposed AI-Supported Productive Homework Framework (ASPH) addresses this challenge through five principles: purposeful instructional design, active cognitive engagement, guided AI integration, student intellectual responsibility, and process-oriented assessment. The framework positions AI as a supportive educational resource while preserving teachers' pedagogical responsibility and students' intellectual independence. Ultimately, the educational value of AI-enhanced homework lies not in technological efficiency but in its capacity to foster meaningful learning, independent thinking, and transferable competencies.