%0 Conference Paper %1 10.1007/978-3-030-44289-7_9 %A Salloum, Said A. %A Alshurideh, Muhammad %A Elnagar, Ashraf %A Shaalan, Khaled %B Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) %C Cham %D 2020 %E Hassanien, Aboul-Ella %E Azar, Ahmad Taher %E Gaber, Tarek %E Oliva, Diego %E Tolba, Fahmy M. %I Springer International Publishing %K educational-datamining review %P 92--102 %T Mining in Educational Data: Review and Future Directions %X One of the developing fields of the present times is educational data mining that pertains to developing methods that help in examining various kinds of data obtained from the educational field. A vital part is played by data mining in the education field, particularly when behavior is being assessed in an online learning setting. This is because data mining is capable of analyzing and identifying the hidden information regarding the data itself, which is very difficult and takes up a lot of time if performed manually. This review has the objective of examining the way data mining was handled by researchers in the past and the most recent trends on data mining in educational research, as well as to evaluate the likelihood of employing machine learning in the field of education. The various limitations inherent in the current research are examined and recommendations are made for future research. %@ 978-3-030-44289-7

@inproceedings{10.1007/978-3-030-44289-7_9, abstract = {One of the developing fields of the present times is educational data mining that pertains to developing methods that help in examining various kinds of data obtained from the educational field. A vital part is played by data mining in the education field, particularly when behavior is being assessed in an online learning setting. This is because data mining is capable of analyzing and identifying the hidden information regarding the data itself, which is very difficult and takes up a lot of time if performed manually. This review has the objective of examining the way data mining was handled by researchers in the past and the most recent trends on data mining in educational research, as well as to evaluate the likelihood of employing machine learning in the field of education. The various limitations inherent in the current research are examined and recommendations are made for future research.}, added-at = {2020-11-01T20:49:42.000+0100}, address = {Cham}, author = {Salloum, Said A. and Alshurideh, Muhammad and Elnagar, Ashraf and Shaalan, Khaled}, biburl = {https://www.bibsonomy.org/bibtex/298dbe16e51f8b06554f8da67ae11fec8/brusilovsky}, booktitle = {Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020)}, description = {Mining in Educational Data: Review and Future Directions | SpringerLink}, editor = {Hassanien, Aboul-Ella and Azar, Ahmad Taher and Gaber, Tarek and Oliva, Diego and Tolba, Fahmy M.}, interhash = {9c069ae785c681466e7f7adc31e1b7b2}, intrahash = {98dbe16e51f8b06554f8da67ae11fec8}, isbn = {978-3-030-44289-7}, keywords = {educational-datamining review}, pages = {92--102}, publisher = {Springer International Publishing}, timestamp = {2020-11-01T20:49:42.000+0100}, title = {Mining in Educational Data: Review and Future Directions}, year = 2020 }