Improving Quality in Educational Processes and Providing a New Knowledge using Data Mining Techniques
Keywords:
Data mining techniques; Higher Education Institutes; Educational Processes; Educational Data Mining; Decision support, CRISP-DM methodologyAbstract
One of the major challenges that Higher Education Institutions (HEI) faces is to improve the quality of their
educational methods. Thus, it is vital for the administration of the organizations to set new approaches and plans for a
improved management of the current processes. Furthermore, the managerial decision is becoming more difficult as
the complexity of educational objects increase. The purpose of this study is to recommend a way to provision the
administration of a HEI by providing new knowledge related to the educational processes using data mining
techniques. This knowledge can be extracted among other from educational data that derive from the evaluation
processes that each department of a HEI conducts. These data can be originated in educational databases, in students’
questionnaires or in faculty members’ records. This paper presents the skills of data mining in the context of a Higher
Education Institute and efforts to discover new explicit knowledge by applying data mining techniques to educational
data of Technological Educational Institute. The data used for this study come from students’ questionnaires scattered
in the classes within the evaluation process of each department of the Institute.