Project 138

Project Summary

How can computers help students write better? The goal of this challenge is to design a program that will classify argumentative elements in student writing as “effective,” “adequate,” or “ineffective.” The research team for this project will create a model trained on data that is representative of the 6th-12th grade population in the United States to help pave the way for students to receive enhanced feedback on their argumentative writing. With automated guidance, students can complete more assignments and ultimately become more confident, proficient writers.

The research team will consider both the accuracy of classification and computational efficiency in which efficiency is determined using a combination of accuracy and the speed at which models are able to generate these predictions. This double focus is due to the fact that highly accurate models are often computationally heavy. Such models have a stronger carbon footprint and frequently prove difficult to utilize in real-world educational contexts, since most educational organizations have limited computational capabilities. The research team for this project might be composed of individuals with interests or specialization in language and rhetoric, education, software engineering, data science, and electrical engineering.

Sustainable Development Goals