Computational Approaches to Analyzing Student performance: Methods and Applications

This session will describe computational approaches to analyzing written and spoken content and how to apply the analyses for a range of educational applications.   It will introduce approaches using Latent Semantic Analysis as well as other natural language processing and machine learning techniques and how to use them to analyze both the coverage of content information and the quality of student expression.   It will further discuss criteria for evaluating performance of the computational methods against educational criteria.    As the approaches are introduced, the session will also discuss how to incorporate the approaches into applications such as automated essay scoring, team performance analysis in live and virtual environments, matching readers to text and standards, and analysis of text complexity.

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