Decision tree grafting from the all-tests-but-one partition
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Predicting failure: a case study in co-blogging
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Course signals at Purdue: using learning analytics to increase student success
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Towards effective tutorial feedback for explanation questions: a dataset and baselines
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Analysis of collaborative writing processes using revision maps and probabilistic topic models
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Formative assessment and learning analytics
Proceedings of the Third International Conference on Learning Analytics and Knowledge
STEMscopes: contextualizing learning analytics in a K-12 science curriculum
Proceedings of the Third International Conference on Learning Analytics and Knowledge
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Real-time formative assessment of student learning has become the subject of increasing attention. Students' textual responses to short answer questions offer a rich source of data for formative assessment. However, automatically analyzing textual constructed responses poses significant computational challenges, and the difficulty of generating accurate assessments is exacerbated by the disfluencies that occur prominently in elementary students' writing. With robust text analytics, there is the potential to accurately analyze students' text responses and predict students' future success. In this paper, we present WriteEval, a hybrid text analytics method for analyzing student-composed text written in response to constructed response questions. Based on a model integrating a text similarity technique with a semantic analysis technique, WriteEval performs well on responses written by fourth graders in response to short-text science questions. Further, it was found that WriteEval's assessments correlate with summative analyses of student performance.