In this chapter, the data mining method in the field of education will be examined, an emerging technology. In this study, studies conducted since 2011 using data mining method, one of the developing technologies, and the results obtained from these studies will be examined in order to increase the success in the field of education. What kind of data has been used in data mining application in the field of education, which algorithms have been used to analyze these data and the success cases obtained from these algorithms will be examined. By examining the results obtained from these studies, it will be examined which algorithms are more successful in the analysis to be obtained. It is aimed to identify the deficiencies that affect the success in the field of education. This study is aimed to be a guide in determining the work to be done to increase the success in the education sector and in determining the algorithms that can be preferred in order to achieve more successful results in these studies.
TopIntroduction
In order to achieve social success, educational success and quality should also be increased.
Education has an important role in forming the future of societies. In order to create a successful society, the importance of education should be increased and it should be aimed to raise individuals with a high level of education. With the regulations in the field of education, a more conscious society can be created by raising more conscious individuals.
In the literature various training methods have been tried in order to increase the quality of education and to reduce the failures. Education methods are changed according to students' success in learning methods. In addition, educational methods also change with the change in the ways people access information.
With the development of technology, emerging technologies are used in education. This situation provides easier access to information. With the wide emerging technology opportunities, an education method is used for students to learn more by research. In addition, it enabled the training to be done in a more visual way. Instead of rote learning system, education methods that enable students to think more, question events and get to know themselves better are preferred.
Emerging technologies are used to increase the quality of education and to find the causes of failures. By using these technologies, factors that cause failure can be identified and necessary arrangements can be made to increase success. In addition, following the current success rate with emerging technologies can be done more easily. Technologies such as artificial intelligence, robotics, deep learning, cloud computing, big data, and data mining can be considered as emerging technologies.
In this chapter, data mining methods in the field of education will be examined an emerging technology. It is possible to convert data that does not make any sense to meaningful information by processing it with data mining. With data mining, seemingly meaningless data is transformed into information, so that the missing parts are detected and the correct solution methods are found more easily. By using data mining in the field of education, the causes of failures will be determined more easily and what needs to be done to increase success will be examined.
In this study, studies since 2011 using data mining method, one of the developing technologies, and the results obtained from these studies will be examined in order to increase the success in the field of education. The answers of the questions of what kind of data has been used in data mining application in the field of education, which algorithms have been used to analyze these data and the success cases obtained from these algorithms will be examined. By examining the results obtained from these studies, it will be examined which algorithms are more successful in the analysis to be obtained. It is aimed to identify the deficiencies that affect the success in the field of education. This study is aimed to be a guide in determining the work to be done to increase the success in the education sector and in determining the algorithms that can be preferred in order to achieve more successful results in these studies.
2011
In Baradwaj & Pal (2011), it is aimed to evaluate student performance by using Decision Tree (DT) method. In Pandey & Pal (2011a), it is aimed to analyze the performance of the student by using Bayes algorithm. While Microsoft SQL 2005 is used in database management, MATLAB is used for programming. In Pandey & Pal, (2011b) an analysis was made with the association rule since the study aimed to find the relationship between the items and show the relationship between them. In (Sarıman, 2011), the clustering algorithms were compared and a better evaluation was observed even if the k-medoids clustering algorithm worked in a scattered cluster compared to k-means algorithm.
In Aher & L.M.R.J., (2011) ZeroR algorithm was used in classification and density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm was used in the clustering of the students. In Baradwaj & Pal, (2011), Naive Bayes (NB) algorithm was used to select the best subset of variables. In (Sarıman, 2011b), “Flags” data set from UCI Machine Learning Repository database was used. In Aher & L.M.R.J., (2011b), the data of the students in the database of the last year students were used for the Information Technologies UG course. Data were collected on a variety of subjects, including his university exam achievements. In (Baradwaj & Pal, 2011), the data set was created with the information obtained from the questionnaire and university database of 300 students from five different universities.