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003			EG-GiCUC
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008			220216s2021 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.20.03.M.Sc.2021.Ka.E
100	0		_aKamilia Hosni Hussien Awad
245	1	0	_aEnhance the adaptive learning using semantic technology / _cKamilia Hosni Hussien Awad ; Supervised Abeer Mohamed Elkorany , Haitham Safwat Hamza
246	1	5	_aتعزيز التعلم التكيفى باستخدام التكنولوجيا الدلالية
260			_aCairo : _bKamilia Hosni Hussien Awad , _c2021
300			_a90 P . : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Computer Science
520			_aAdaptive learning is one of the most widely used data driven approach to teaching and it received an increasing attention over the last decade. It aims to meet the student{u2019}s characteristics by tailoring learning courses materials and assessment methods. In order to determine the student{u2019}s characteristics, it is necessary to detect their learning styles according to VAK (Visual, Auditory or Kinesthetic) learning style. Adaptive learning includes the adaptation of all learning components. Assessment is one of the most important learning components that could enhance the learning outcomes. Implementing alternative types of assessment to meets students{u2019} characteristics and abilities lies under the umbrella of adaptive learning. In this research, an integrated model that utilizes both semantic technology and machine learning clustering methods is developed in order to cluster students and detect their learning styles then recommend suitable assessment method(s) accordingly. In order to measure the effectiveness of the proposed model, a set of experiments were conducted on real dataset (Open University Learning Analytics Dataset). Experiments showed that the proposed model is able to cluster students according to their different learning activities with an accuracy that exceeds 95% and predict their relative assessment method(s) with an average accuracy equals to 93%
530			_aIssued also as CD
650		0	_aSemantic analysis
653		4	_aAdaptive learning
653		4	_aMachine learning
653		4	_aSemantic technology
700	0		_aAbeer Mohamed Elkorany , _eSupervising
700	0		_aHaitham Safwat Hamza , _eSupervising
856			_uhttp://172.23.153.220/th.pdf
905			_aAmira _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c84244 _d84244