A Probabilistic Relational Student Model for Virtual Laboratories
ENC '05 Proceedings of the Sixth Mexican International Conference on Computer Science
Supporting CSCL with automatic corpus analysis technology
CSCL '05 Proceedings of th 2005 conference on Computer support for collaborative learning: learning 2005: the next 10 years!
Reading level assessment using support vector machines and statistical language models
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Modeling local coherence: An entity-based approach
Computational Linguistics
Automatic evaluation of text coherence: models and representations
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Using entity-based features to model coherence in student essays
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
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In many cases, academic programs or courses conclude with a thesis or research proposal text, elaborated by students. The review of such texts is a heavy load, especially at initial stages of drafting. This paper proposes a model that allows linguistic and structural review of some essential elements in proposal drafts of undergraduate students. The model aims to support the review from vocabulary to the argumentation in the draft, and is part of an intelligent tutor to monitor student progress. This work presents the initial results in terms of lexical and global coherence analysis of proposal drafts of students. Lexical analysis is done in terms of lexical density, lexical diversity, and sophistication. Global coherence is evaluated using the Latent Semantic Analysis technique. Our results show that the level reached so far by the analyzer is adequate to support the review, taking into account for one section the level of agreement with human reviewers.