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Livieris, Ioannis E.; Drakopoulou, Konstantina; Tampakas, Vassilis T.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Journal of Educational Computing Research, 2019
Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…
Descriptors: Secondary School Students, Academic Achievement, Teaching Methods, Student Behavior
Blagdanic, Casandra; Chinnappan, Mohan – Australian Mathematics Teacher, 2013
Numeracy in schools is becoming an increasingly important part of mathematics learning and teaching. This is because educators want students to engage with mathematical concepts more deeply, use mathematics to make sense of their environment and make decisions that are based on the analysis of mathematical information. In order to be numerate,…
Descriptors: Statistical Analysis, Statistics, Data Interpretation, Numeracy
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection