A Systematic Review of Natural Language Processing Applications in Personalized Learning

• In Event: DELT- Analytics and Assessments for Learning

Short Description

A systematic review of 2010–2022 peer-reviewed journal articles shows how natural language processing (NLP) has personalized learning. NLP analyzes student data, generates personalized feedback, recommends adaptive content, facilitates natural language interactions, and creates personalized learning environments. NLP helps teachers identify student needs, target interventions, and personalize instruction. Data quality, quantity, NLP algorithm accuracy and reliability, and student data ethics determine NLP's effectiveness in personalized learning environments.

Author

• Contributor: Ji Hyun Yu, University of North Texas