000			02328nam a22003017a 4500
003			KOHA
005			20221226090245.0
008			220928d2022 cy ||||| m||| 00| 0 eng d
040			_aCY-NiCIU _beng _cCY-NiCIU _erda
041			_aeng
090			_aD 321 _bC24 2022
100	1		_aÇağataylı, Mustafa
245	1	2	_aA MACHINE LEARNING APPROACH TO PREDICT ACADEMIC SUCCESS IN HIGHER EDUCATION USING THE BIG FIVE PERSONALITY TRAITS / _cMustafa ÇAĞATAYLI; Supervisor: Assoc. Prof. Dr. Erbug Çelebi
264			_c2022
300			_a121 sheets; _c31 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
502			_aThesis (PhD) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems Department
504			_aIncludes bibliography (sheets 91-111)
520			_aABSTRACT Using students' previous course grades is the most common method of forecasting academic performance in higher education. A novel strategy is proposed in this study to predict academic success in higher education using personality traits instead of existing course grades. The primary focus of this multidisciplinary project is to use Machine Learning to combine the benefits of psychology and computer science to predict the academic success of students in higher education institutions. The proposed technique was tested on 20 distinct course categories using Big Five features as personality traits of 2,575 higher education students. We find that Machine Learning may be used to predict academic success while taking into account all five Big Five personality trait dimensions. The Big Five traits of prospective students can be used to predict higher education student achievement for the applied department using our proposed method. Our strategy can be used in a variety of departments or course groups. This approach could be enhanced such that higher education institutions can even recommend departments to students to help them succeed.
650		0	_aPersonality _vDissertations, Academic
650		0	_aEducation, Higher _vDissertations, Academic
650		0	_aMachine learning _vDissertations, Academic
700	1		_aÇelebi, Erbuğ _esupervisor
942			_2ddc _cTS
999			_c285301 _d285301