Application of Text Mining Techniques for Evaluating Examination Question Paper

摘要：

Academic institutions regularly record huge amount of data relating to various university based examinations for different courses. We address the problem of evaluating the question papers by analyzing each question of a question paper on different criteria. University specified syllabus file for each subject in a particular semester along with the Blooms Taxonomy concept is used as a guideline in evaluating the difficulty level of the examination question paper in that subject. Text mining techniques are used to extract keywords from textual contents in the syllabus file and question paper. A tool named Mining Exam Question Paper Based on Syllabus (MEQPBS) is implemented. This tool can be used by concerned authorities to evaluate the examination question papers of theoretical papers.

关键词： Blooms Taxonomy Educational Data Text Mining Stemming Information Extraction

作者: Dimple V.Paul Jyoti D.Pawar

作者单位: Department of Computer Science D.Ms College of Science, Arts and Commerce Mapusa, Goa, India Department of Computer science and Technology Goa University Taleigao,Goa,lndia

会议类型: 国际会议

会议名称: 2011 International Conference on Database and Data Mining(ICDDM 2011)(2011年数据库和数据挖掘国际会议)

会议地点: 三亚

会议语种:英文

页码: 74-78

在线出版日期: 2011-03-25（万方平台首次上网日期，不代表论文的发表时间）