Factors affecting students' performance in higher education: a systematic review of predictive data mining techniques
Predicting the students' performance has become a challenging task due to the increasing
amount of data in educational systems. In keeping with this, identifying the factors affecting …
amount of data in educational systems. In keeping with this, identifying the factors affecting …
[PDF][PDF] Application of big data in education data mining and learning analytics–a literature review
The usage of learning management systems in education has been increasing in the last
few years. Students have started using mobile phones, primarily smart phones that have …
few years. Students have started using mobile phones, primarily smart phones that have …
Prediction of benign and malignant breast cancer using data mining techniques
Breast cancer is the second most leading cancer occurring in women compared to all other
cancers. Around 1.1 million cases were recorded in 2004. Observed rates of this cancer …
cancers. Around 1.1 million cases were recorded in 2004. Observed rates of this cancer …
[PDF][PDF] Educational data mining & students' performance prediction
AA Saa - … journal of advanced computer science and …, 2016 - pdfs.semanticscholar.org
It is important to study and analyse educational data especially students' performance.
Educational Data Mining (EDM) is the field of study concerned with mining educational data …
Educational Data Mining (EDM) is the field of study concerned with mining educational data …
Assessment and evaluation of different machine learning algorithms for predicting student performance
YA Alsariera, Y Baashar, G Alkawsi… - Computational …, 2022 - Wiley Online Library
Student performance is crucial to the success of tertiary institutions. Especially, academic
achievement is one of the metrics used in rating top‐quality universities. Despite the large …
achievement is one of the metrics used in rating top‐quality universities. Despite the large …
[PDF][PDF] Educational Data Mining and Learning Analytics: differences, similarities, and time evolution
LC Liñán, ÁAJ Pérez - RUSC …, 2015 - educationaltechnologyjournal …
Technological progress in recent decades has enabled people to learn in different ways.
Universities now have more educational models to choose from, ie, b-learning and e …
Universities now have more educational models to choose from, ie, b-learning and e …
Systematic ensemble model selection approach for educational data mining
A plethora of research has been done in the past focusing on predicting student's
performance in order to support their development. Many institutions are focused on …
performance in order to support their development. Many institutions are focused on …
Early prediction of heart diseases using data mining techniques
DV Chaurasia, S Pal - Caribbean journal of Science and …, 2013 - papers.ssrn.com
Largest-ever study of deaths shows heart diseases have emerged as the number one killer
in world. About 25 per cent of deaths in the age group of 25-69 years occur because of heart …
in world. About 25 per cent of deaths in the age group of 25-69 years occur because of heart …
A critical assessment of imbalanced class distribution problem: The case of predicting freshmen student attrition
Predicting student attrition is an intriguing yet challenging problem for any academic
institution. Class-imbalanced data is a common in the field of student retention, mainly …
institution. Class-imbalanced data is a common in the field of student retention, mainly …
Quantitative approach to collaborative learning: Performance prediction, individual assessment, and group composition
The benefits of collaborative learning, although widely reported, lack the quantitative rigor
and detailed insight into the dynamics of interactions within the group, while individual …
and detailed insight into the dynamics of interactions within the group, while individual …