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Automated Essay Scoring and Flexible Learning

Automated Essay Scoring and Flexible Learning
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Author(s): Raymond K.Y. Li (Monash University, Australia) and Kwang-Hoon Oh (Monash University, Australia)
Copyright: 2003
Pages: 4
Source title: Information Technology & Organizations: Trends, Issues, Challenges & Solutions
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-066-0.ch091
ISBN13: 9781616921248
EISBN13: 9781466665330

Abstract

Rapid advancements in networking and computer technology over recent years have changed the ways that education can be delivered. “Flexible learning” is now a reality. Assessment is an important element in the process of learning, irrespective of the delivery methods involved. Test methods, such as multiple-choice tests and matching items, enable simple assessment of a student’s learning by a computer. However, there are limitations to these methods. Traditionally, essay testing has been used by educators to assess students’ knowledge, especially within higher education. This paper examines an automated essay scoring methods utilizing Latent Semantic Analysis. Computation experience indicates that a LSA system can be used to automatically score long essays in a higher education environment. The findings provide an insight into how LSA works and the problems associated with the application of a LSA model to essay scoring.

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