Predicting Students' Degree Completion Using Decision Trees

Educational Data Mining (EDM) helped institutions to improve students' performance by predicting student's future learning behavior. To benefit from this, the researchers conducted this study to predict the successful degree completion and provide early intervention as necessary. Decision Tree algorithm provided by WEKA is used to build the model using students' data such as Entrance Exam Results, gender, school type where they graduated high school and final grades from English 1, Algebra and major subjects. Students who entered the University from school years 2012-2013, 2013-2014, 2014-2015 and 2015-2016 were selected. RandomForest suited best for the model and desktop application was designed and evaluated as Outstanding in terms of Efficiency, Accuracy and User Friendliness.

What System Safety Engineering Can Learn from the Columbia Accident

An accident investigation allows a view into an organization that is normally not possible. The strong system safety program established at NASA after the Apollo fire has evolved into a program in which the name remains but most of the important safety management and engineering functions have disappeared or are performed by contractors. The title remains, but the essence is gone