A Data Mining Approach to Inquiry Based Inductive Learning Practice in Engineering Education

Inquiry based Inductive learning methodology is one of the best technique especially for the engineering students who are expected to solve real world problems. But it is very difficult to standardize a particular learning methodology for an institution with diverse attitude, diverse characteristics, diverse languages, diverse financial back grounds, and diverse cultural scenario with variable educational standard of the students. As the teaching methodology depends on the content and time as well as learners' varied style of learning, the same learner may prefer inductive teaching for one topic and deductive approach for the other topic. This paper initiates a sample study that is taken for a particular institution, in the particular environment, for the particular batch and particular set of students. The sample data are collected from a classroom by distributing the questionnaire attempted by two different batches of student having questions pertaining to Inquiry based and deductive learning. The system is developed and tested twice after teaching the content using inductive method and implemented using attribute relevance, discriminant rules of class discrimination mining. The results are visualized through bar charts and shows that the two batches of learners of different years have different learning characteristics.