A Review of Digital Learning Environments for Teaching Natural Language Processing in K-12 Education
It addresses the need for effective NLP education tools for K-12 students, but it is incremental as it reviews existing literature without introducing new methods or data.
This paper reviews digital learning environments for teaching Natural Language Processing (NLP) in K-12 education, analyzing existing tools, their support for NLP tasks, and their explainability and evaluation results to guide future research and development.
Natural Language Processing (NLP) plays a significant role in our daily lives and has become an essential part of Artificial Intelligence (AI) education in K-12. As children grow up with NLP-powered applications, it is crucial to introduce NLP concepts to them, fostering their understanding of language processing, language generation, and ethical implications of AI and NLP. This paper presents a comprehensive review of digital learning environments for teaching NLP in K-12. Specifically, it explores existing digital learning tools, discusses how they support specific NLP tasks and procedures, and investigates their explainability and evaluation results in educational contexts. By examining the strengths and limitations of these tools, this literature review sheds light on the current state of NLP learning tools in K-12 education. It aims to guide future research efforts to refine existing tools, develop new ones, and explore more effective and inclusive strategies for integrating NLP into K-12 educational contexts.