DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE
Although data mining has been successfully implemented in the business world for some time now, its use in higher education is still relatively new, i.e. its use is intended for identification and extraction of new and potentially valuable knowledge from the data. Using data mining the aim was to d...
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| Format: | Article |
| Language: | English |
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Faculty of Economics, University of Tuzla
2012-05-01
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| Series: | Economic Review |
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| Online Access: | http://er.ef.untz.ba/index.php/er/article/view/174 |
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| _version_ | 1823861258817896448 |
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| author | Edin Osmanbegović Mirza Suljić |
| author_facet | Edin Osmanbegović Mirza Suljić |
| author_sort | Edin Osmanbegović |
| collection | DOAJ |
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Although data mining has been successfully implemented in the business world for some time now, its use in higher education is still relatively new, i.e. its use is intended for identification and extraction of new and potentially valuable knowledge from the data. Using data mining the aim was to develop a model which can derive the conclusion on students' academic success. Different methods and techniques of data mining were compared during the prediction of students' success, applying the data collected from the surveys conducted during the summer semester at the University of Tuzla, the Faculty of Economics, academic year 2010-2011, among first year students and the data taken during the enrollment. The success was evaluated with the passing grade at the exam. The impact of students' socio-demographic variables, achieved results from high school and from the entrance exam, and attitudes towards studying which can have an affect on success, were all investigated. In future investigations, with identifying and evaulating variables associated with process of studying, and with the sample increase, it would be possible to produce a model which would stand as a foundation for the development of decision support system in higher education.
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| format | Article |
| id | doaj-art-6db623b12a094f5b8bd6e0e736747a7c |
| institution | Kabale University |
| issn | 1512-8962 2303-680X |
| language | English |
| publishDate | 2012-05-01 |
| publisher | Faculty of Economics, University of Tuzla |
| record_format | Article |
| series | Economic Review |
| spelling | doaj-art-6db623b12a094f5b8bd6e0e736747a7c2025-02-10T00:31:30ZengFaculty of Economics, University of TuzlaEconomic Review1512-89622303-680X2012-05-01101DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCEEdin Osmanbegović0Mirza Suljić1Faculty of Economics, University of Tuzla, Bosnia and HerzegovinaFaculty of Economics, University of Tuzla, Bosnia and Herzegovina Although data mining has been successfully implemented in the business world for some time now, its use in higher education is still relatively new, i.e. its use is intended for identification and extraction of new and potentially valuable knowledge from the data. Using data mining the aim was to develop a model which can derive the conclusion on students' academic success. Different methods and techniques of data mining were compared during the prediction of students' success, applying the data collected from the surveys conducted during the summer semester at the University of Tuzla, the Faculty of Economics, academic year 2010-2011, among first year students and the data taken during the enrollment. The success was evaluated with the passing grade at the exam. The impact of students' socio-demographic variables, achieved results from high school and from the entrance exam, and attitudes towards studying which can have an affect on success, were all investigated. In future investigations, with identifying and evaulating variables associated with process of studying, and with the sample increase, it would be possible to produce a model which would stand as a foundation for the development of decision support system in higher education. http://er.ef.untz.ba/index.php/er/article/view/174data miningclassificationpredictionstudent successhigher education |
| spellingShingle | Edin Osmanbegović Mirza Suljić DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE Economic Review data mining classification prediction student success higher education |
| title | DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE |
| title_full | DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE |
| title_fullStr | DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE |
| title_full_unstemmed | DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE |
| title_short | DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE |
| title_sort | data mining approach for predicting student performance |
| topic | data mining classification prediction student success higher education |
| url | http://er.ef.untz.ba/index.php/er/article/view/174 |
| work_keys_str_mv | AT edinosmanbegovic dataminingapproachforpredictingstudentperformance AT mirzasuljic dataminingapproachforpredictingstudentperformance |