ELECTROLAB: A NEW DATASET FOR EDUCATIONAL DATA MINING

Bergen KARABULUT¹ , Şeyma CİHAN² , Halil Murat ÜNVER³ , atilla ergüzen ⁴

Engineering education prepares students for life by presenting theoretical and practical knowledge together. A common method is applying laboratory experiments for practicing theoretical knowledge by students. The objective of the laboratory experiments is to gain student the ability of transferring theoretical knowledge to practice and see the differences between theory and practice. However; classical evaluation of laboratory courses has some difficulties in terms of assessing complex input factors related to students. Educational data mining, which has been widely used recently, allows evaluations for student performance to be made easier. Implementing educational data mining for laboratory lesson can be important contributions to the determination of the factors affecting student performance and the structuring of training methods accordingly. In this study, Electronic Circuits Laboratory Course, which is the practice of Electronic Circuits Course as a basic course of Computer Engineering education, were examined. A laboratory data set called ELECTROLAB was created by collecting data from these courses. The first phases of CRISP, the standard for data mining operations, have been implemented on this data set. The data set was prepared and the attributes in the data set were analyzed according to these phases. In the study, R programming language and Weka program were used.

Keywords
Data Mining, Educational Data Mining, Laboratory Dataset, Student Performance, CRISP-DM,