A Study of Improving Mathematics Assessment Readability by using GPT-3

A Study of Improving Mathematics Assessment Readability by using GPT-3

This dataset contains 250 math word problems from EngageNY, and their automated simplifications generated using the GPT-3 engine. There are eight ways each prompt is simplified, and three samples are taken for each prompt. Some API calls can fail or return a blank string. Those responses are omitted. Readability measures for input and output passages are generated using the Common Text Analysis Platform (http://sifnos.sfs.uni-tuebingen.de/ctap/). Text similarity metrics are generated by computing the % of total words between input and output and cosine similarity of the text vectors that GPT-3 embedding API generates.