Enhancing student learning through practical applications of Natural Language Processing

Abstract

The integration of Natural Language Processing into higher education offers significant opportunities to enhance student learning by combining computational thinking with linguistic analysis and critical reflection. This article explores how practical applications of NLP can transform the teaching and learning experience in universities. By engaging students in hands-on projects such as text classification, sentiment analysis, and conversational AI, educators can foster deeper conceptual understanding, interdisciplinary collaboration, and ethical awareness. Practical engagement with NLP tools and real-world data enables learners to bridge theory and practice, develop digital literacy, and cultivate problem-solving skills relevant to the evolving demands of the knowledge economy. The paper argues that experiential approaches to NLP education not only strengthen technical competence but also encourage creativity, social responsibility, and lifelong learning. As a result, teaching NLP through practical applications prepares students to become active contributors to the development of ethical and human-centered artificial intelligence in diverse academic and professional contexts.