Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining and theory
作者：
Highlights：
• A theory-based method for a computational student performance prediction.
• A Genetic Programming model for grade prediction is described and tested.
• Model evaluation suggests high success rates for predicting student grades.
摘要
•A theory-based method for a computational student performance prediction.•A Genetic Programming model for grade prediction is described and tested.•Model evaluation suggests high success rates for predicting student grades.
论文关键词：Learning analytics,Educational data mining,Prediction,CSCL,Activity theory,Genetic Programming
论文评审过程：Available online 24 November 2014.
论文官网地址：https://doi.org/10.1016/j.chb.2014.09.034
