Outcome based predictive analysis of automatic question paper using data mining

In recent years, data mining had become very popular to provide a facility in various fields. Large amount of data elements are stored in the database. Various data mining algorithms are used to classify the data elements and perform some operations to find the best solution on the basis of some relational parameters. One of the automatic architecture designs in this research is to find the solution for examination in terms of level wise question paper. The entire examination process is a vital component for direct assessment of an individual learning. So, preparing a complete test paper and the setup is relatively necessary. Currently, the customary technique of making question paper has been handbook. In current scenario the question paper generation is a manual approach leading to unproductive at times owing to bias, repetition and security concerns. The current paper presents an automatic procedure of question paper group which can be modified, streamlined, synchronized and secured. Each task done by this system is automatic, such that storing space, bias and security is not an apprehension any longer. Earlier, the question paper was generated by concerned subject teacher manually and was very time consuming, man power was required and sometimes the question paper lacked accuracy. Outcome Based Education (OBE) designates what students will know and be intelligent to do, as they advance in a program. The information related to student learning was collected for question paper generation and assessment using OBE. This information can be used to predict students ability, advancements in education system, betterment in teaching method, future interest of student etc. Various data mining classifiers like oneR, ZeroR, J48, Naive Bayes, IBk are used for prediction of the course outcome. The comparative study contains some parameters like time, detection accuracy, classification error etc. to find the performance of the proposed architecture as compared to other techniques to verify the enhancements.