Real-Time Automated Answer Scoring
This addresses the issue of reducing effort and cost in education for teachers and institutions, but it appears incremental as automated scoring has been explored before.
The paper tackles the problem of high evaluation costs for constructed-response assessments by developing a real-time automated answer scoring system that processes raw student answers and scores them, also capturing snapshots of writing progress to analyze thinking trends.
In recent years, the role of big data analytics has exponentially grown and is now slowly making its way into the education industry. Several attempts are being made in this sphere in order to improve the quality of education being provided to students and while many collaborations have been carried out before, automated scoring of answers has been explored to a rather limited extent. One of the biggest hurdles to choosing constructed-response assessments over multiple-choice assessments is the effort and large cost that comes with their evaluation and this is precisely the issue that this project aims to solve. The aim is to accept raw-input from the student in the form of their answer, preprocess the answer, and automatically score the answer. In addition, we have made this a real-time system that captures "snapshots" of the writer's progress with respect to the answer, allowing us to unearth trends with respect to the way a student thinks, and how the student has arrived at their final answer.