A Large Scale Quantitative Exploration of Modeling Strategies for Content Scoring

WS 2017 Nitin MadnaniAnastassia LoukinaAoife Cahill

We explore various supervised learning strategies for automated scoring of content knowledge for a large corpus of 130 different content-based questions spanning four subject areas (Science, Math, English Language Arts, and Social Studies) and containing over 230,000 responses scored by human raters. Based on our analyses, we provide specific recommendations for content scoring... (read more)

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