Applying Semantic Analysis to Training, Education, and Immersive Learning

The last decade has seen major advances in the areas of natural language processing and semantic analysis. Theoretical advances and increased computational power have resulted in applications that detect topics and sentiments in communications, automatically classify unstructured data in enterprise settings, and win Jeopardy contests. This paper surveys how these same methods apply to a variety of problems in education and training. Applications include automatic grading and question generation, guiding the behavior of intelligent tutoring systems, aligning content to competencies and educational standards, and improving search in digital repositories. This paper describes the methods, explains how they are applied and evaluated, and discusses their potential for use virtual worlds and immersive learning environments.