doi: 10.4304/jsw.9.2.429-436
Automated Essay Scoring Using Incremental Latent Semantic Analysis
- 1 School of Information Science and Technology, Beijing Forestry University
- 2 Institute of Automation, Chinese Academy of Sciences
- 3 Institute of Educational Measurement, Beijing Language and Culture University
Abstract
Writing has been increasingly regarded by thetesters of language tests as an important indicator to assessthe language skill of testees. As such tests become more andmore popular and the number of testees becomes larger,it is a huge task to score so many essays by raters. Sofar, many methods have been used to solve this problemand the traditional method is Latent Semantic Analysis(LSA). In this paper, we introduce a new incrementalmethod of LSA to score essays effectively when the datasetis massive. By comparison of the traditional method andour new incremental method, concerning the running timeand memory usage, experimental results make it obviousthat the incremental method has a huge advantage over thetraditional method. Furthermore, we use real corpora oftest essays submitted to the MHK test (Chinese ProficiencyTest for Minorities), to demonstrate that the incrementalmethod is not only efficient but also effective in performingLSA. The experimental results also show that when usingincremental LSA, the scoring accuracy can reach 88.8%.
Keywords
- automated essay scoring
- incremental lat
How to Cite
Mingqing Zhang, Shudong Hao, Yanyan Xu, Dengfeng Ke, and Hengli Peng, "Automated Essay Scoring Using Incremental Latent Semantic Analysis," Journal of Software, vol. 9, no. 2, pp. 429-436, 2014. https://doi.org/ 10.4304/jsw.9.2.429-436
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).