Predicting library of congress classifications from library of congress subject headings
Journal of the American Society for Information Science and Technology
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
NLTK: the Natural Language Toolkit
ETMTNLP '02 Proceedings of the ACL-02 Workshop on Effective tools and methodologies for teaching natural language processing and computational linguistics - Volume 1
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An online class provides a unique opportunity for the students to participate in the class at their own convenience. However, the students have to be kept motivated by providing the tools to enable discussions related to the class topics. This paper implements and presents a model coupled with data mining techniques that will predict how the students are faring in the classroom discussions. The model provides feedback on which students are active in their online discussions, what topics they are discussing, the relevance of those discussions, and share the information with all those involved in the class. The techniques presented in this work can be applied to any online class. However, presenting this work in the context of a data mining class is especially rewarding. Students can use their discussions themselves as a case study and apply them in the context of various data mining and text mining algorithms covered in the class. The framework not only aides an instructor in understanding the student interest and participation in an online class, but also helps the students with feedback on their posts with respect to the others.