Evaluating the effectiveness of educational data mining techniques for early prediction of students' academic failure in introductory programming courses

作者：

Highlights：

• We evaluated effectiveness of mining techniques to early predict students' failures.

• We collected data from two independent introductory programming courses.

• The results showed that the Support Vector Machine reached highest effectiveness.

摘要

•We evaluated effectiveness of mining techniques to early predict students' failures.•We collected data from two independent introductory programming courses.•The results showed that the Support Vector Machine reached highest effectiveness.

论文关键词：Artificial intelligence in education,Automatic instructional planner,Automatic prediction,Educational data mining,Interactive learning environment,Learner modeling

论文评审过程：Received 13 January 2016, Revised 16 January 2017, Accepted 26 January 2017, Available online 4 February 2017, Version of Record 30 March 2017.

论文官网地址：https://doi.org/10.1016/j.chb.2017.01.047