Abstract
Human essay grading is a laborious task that can consume much time and effort. Automated Essay Scoring (AES) has thus been proposed as a fast and effective solution to the problem of grading student writing at scale. However, because AES typically uses supervised machine learning, a human-graded essay corpus is still required to train the AES model. Unfortunately, such a graded corpus often does not exist, so creating a corpus for machine learning can also be a laborious task. This paper presents an investigation of replacing the use of human-labeled essay grades when training an AES system with two automatically available but weaker signals of essay quality: word count and topic distribution similarity. Experiments using two source-based essay scoring (evidence score) corpora show that while weak supervision does not yield a competitive result when training a neural source-based AES model, it can be used to successfully extract Topical Components (TCs) from a source text, which are required by a supervised feature-based AES model. In particular, results show that feature-based AES performance is comparable with either automatically or manually constructed TCs.- Anthology ID:
- 2021.bea-1.9
- Volume:
- Proceedings of the 16th Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Editors:
- Jill Burstein, Andrea Horbach, Ekaterina Kochmar, Ronja Laarmann-Quante, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Helen Yannakoudakis, Torsten Zesch
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 85–96
- Language:
- URL:
- https://aclanthology.org/2021.bea-1.9
- DOI:
- Cite (ACL):
- Haoran Zhang and Diane Litman. 2021. Essay Quality Signals as Weak Supervision for Source-based Essay Scoring. In Proceedings of the 16th Workshop on Innovative Use of NLP for Building Educational Applications, pages 85–96, Online. Association for Computational Linguistics.
- Cite (Informal):
- Essay Quality Signals as Weak Supervision for Source-based Essay Scoring (Zhang & Litman, BEA 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.bea-1.9.pdf