Knowledge Discovery in Higher Educational Big Dataset

Literature Review

In recent years, there has been a limited literature on data mining in education. Romero did a survey from 1995 to 2005 on educational data mining (Romero & Ventura, 2007). He reported data can come from two types of educational systems: Traditional classroom and distance education (Romero & Ventura, 2007). Besides he pointed educational data mining is an immature research area and it is essential more specialized work.

To determine the use of data mining in educational environment, Vranic, Pintar, et al (2007) presented how data mining techniques can be used in the academic environment to develop some aspects of education quality.

In 2009 Vialardi did a research on the use of data mining techniques for recommendation system used by students for decision making on their academic programs. The main point of this research is on extracting knowledge form students’ performance (Vialardi, Bravo, Shafti, & Ortigosa, 2009). Their work contains data preprocessing and pattern extraction and evaluation to discover patterns that can be used for recommendation systems intended for students.

In other case, Baepler and Murdoch pointed how data mining techniques and their results can be useful to those who are in the education domain (Baepler & Murdoch, 2010). They reported many historians have argued that common data mining techniques which used in higher education are clustering, classification, visualization, and association analysis (Baepler & Murdoch, 2010). Their work is largely expletory and focuses more on the prospective of these analyses.