Practical Tools for Large-Scale Evaluation of Text Data in Randomized Trials in Education

The purpose of this grant is to provide machine learning tools to improve the statistical power of an education impact analysis that relies on human-scoring of text passages written by students. Machine learning can be particularly useful in studies that have more text data than time, money, and/or coders to score all of the text data by human raters. By using the text and scores provided by the available human raters to train a machine learning algorithm, computer-scoring would then be used to score the remaining text passages. This would both increase the statistical power of text-based studies and leverage key aspects of machine learning to run additional analyses for investigating potential text pattern differences between the groups.