Natural Language Processing Core Concepts for Educational Applications

Abstract

Natural Language Processing (NLP) is rapidly transforming the educational landscape by enabling automated assessments, intelligent tutoring systems, and personalized language support. This chapter highlights how core NLP tasks, such as tokenization, syntactic parsing, and transformer-based modeling, are increasingly embedded in tools that support both learners and educators. These innovations offer significant benefits, including workload reduction for teachers, enhanced feedback mechanisms, and more adaptive, interactive learning environments. However, the integration of NLP in education must be approached with a balance of enthusiasm and caution. Pedagogical alignment, ethical oversight, and technical limitations must be carefully managed to ensure NLP tools supplement rather than replace human instruction. Future directions include multilingual and multimodal systems, low-resource language support, and bias mitigation strategies to ensure inclusion, transparency, and data privacy.