DIGITAL FEEDBACK SYSTEMS FOR IMPROVING READING-BASED WRITING TASKS

This article examines the role of digital feedback systems in enhancing reading-based writing tasks. It synthesizes current evidence on automated and semi-automated feedback tools that target comprehension, analysis, synthesis, and argumentative writing skills rooted in reading. The paper evaluates system features (diagnostic feedback, formative comments, adaptive prompts, and analytics), pedagogical integration strategies, and impacts on writing quality, metacognition, and revision behavior. Findings indicate that well-designed digital feedback systems can accelerate skill development when combined with teacher mediation, scaffolds for source use, and iterative revision cycles. Challenges include aligning feedback with curricular goals, ensuring feedback specificity and interpretability, addressing source‑based plagiarism, and mitigating equity issues related to access and algorithmic bias. The article concludes with recommendations for design principles, classroom implementation, and directions for future research.