A Comparative Study of Question Bank Classification based on Revised Bloom’s Taxonomy using SVM and K-NN

Education is not only about learning the facts, but the training of the mind to think. Based on the thinking ability of the person, the “Cognitive skill Domain” of the Revised Bloom's Taxonomy tries to distinguish the process of learning into six different levels. These levels are ordered in the increasing level of complexity. Lorin Anderson and David Krathwohl are the primary authors of the revisions to which is widely known as Bloom's Taxonomy that defines an ordering of cognitive skill and knowledge skills. Questions are the primordial component, it can be used to examine the skills and levels of the student. The primary aim of this paper is to make a comparative study of question bank classification based on Revised Bloom's Taxonomy using the machine learning techniques called SVM and K-NN in an attempt to achieve better performance and higher accuracy levels. In order to classify questions into the taxonomy the paper describes the various tests performed namely grammar check, in context check. This work helps the students to improve their thinking and questioning ability and the tutor for setting the objectives of the course and to make assessments.