Using a MaxEnt Classifier for the Automatic Content Scoring of Free-Text Responses
- Educational Testing Service, Rosedale Road, Princeton NJ 08541 (United States)
Criticisms against multiple-choice item assessments in the USA have prompted researchers and organizations to move towards constructed-response (free-text) items. Constructed-response (CR) items pose many challenges to the education community - one of which is that they are expensive to score by humans. At the same time, there has been widespread movement towards computer-based assessment and hence, assessment organizations are competing to develop automatic content scoring engines for such items types - which we view as a textual entailment task. This paper describes how MaxEnt Modeling is used to help solve the task. MaxEnt has been used in many natural language tasks but this is the first application of the MaxEnt approach to textual entailment and automatic content scoring.
- OSTI ID:
- 21506994
- Journal Information:
- AIP Conference Proceedings, Vol. 1305, Issue 1; Conference: 30. international workshop on Bayesian inference and maximum entropy methods in science and engineering, Chamonix (France), 4-9 Jul 2010; Other Information: DOI: 10.1063/1.3573647; (c) 2011 American Institute of Physics; ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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