Vilas P. Mahatme and K. K. Bhoyar
Questions Categorization in ELearning Environment Using Data Mining Technique
93 - 97
2016
10
1
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10003384
https://publications.waset.org/vol/109
World Academy of Science, Engineering and Technology
Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, eexamination systems are being widely adopted in academic environments. Multiplechoice tests are extremely popular. Moving away from traditional examinations to eexamination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in eexamination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in elearning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and elearning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Open Science Index 109, 2016