ENHANCING WRITING SKILLS THROUGH AUTOMATED FEEDBACK: AN EXPLORATION OF ARTIFICIAL INTELLIGENCE AND NATURAL LANGUAGE PROCESSING IN LANGUAGE LEARNING

Abstract

This paper examines the transformative potential of artificial intelligence (AI) and natural language processing (NLP) in revolutionizing writing instruction through automated feedback systems. AI-driven tools offer immediate, personalized feedback on grammar, style, and coherence, thereby enhancing the efficiency and effectiveness of writing processes in educational contexts. Drawing on constructivist and socio-cultural theories, the study explores how these technologies support interactive learning experiences akin to human instruction, as evidenced by applications such as Automated Writing Evaluation (AWE) systems and Intelligent Tutoring Systems (ITS). Despite these advancements, challenges remain in ensuring the accuracy of feedback, addressing biases inherent in training data, and navigating ethical concerns surrounding student data privacy and AI use in education. Practical implications for educators include the necessity for ongoing professional development in AI integration, leveraging data analytics for informed decision-making in curriculum design, and establishing robust frameworks for ethical data handling. By proactively addressing these challenges, educators can effectively harness the potential of AI and NLP to optimize learning outcomes and cultivate essential writing skills across diverse educational settings. This paper underscores the importance of strategic integration and ethical considerations in leveraging AI and NLP to meet the evolving demands of writing instruction in the digital age.