Abstract
This paper presents the approach to automated analysis of student argument diagrams to be used in the Genetics Argumentation Inquiry Learning (GAIL) system. Student arguments are compared to expert arguments automatically generated using an existing argument generator developed previously for the GenIE Assistant project. A prototype argument analyzer was implemented for GAIL. Weaknesses in student arguments are identified using non-domain-specific, non-content-specific rules that recognize common error types. © 2013 Springer-Verlag Berlin Heidelberg.
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Green, N. L. (2013). Towards automated analysis of student arguments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7926 LNAI, pp. 591–594). Springer Verlag. https://doi.org/10.1007/978-3-642-39112-5_66
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