Using gameplay data to examine learning behavior patterns in a serious game
作者：
Highlights：
• Sequential pattern mining identifies different problem-solving stages in a game.
• Frequent patterns indicate students' engagement in the process of scientific inquiry.
• Problem-solving strategies are different between low- and high-performing students.
• Educational contexts should be incorporated into pattern mining algorithms.
摘要
•Sequential pattern mining identifies different problem-solving stages in a game.•Frequent patterns indicate students' engagement in the process of scientific inquiry.•Problem-solving strategies are different between low- and high-performing students.•Educational contexts should be incorporated into pattern mining algorithms.
论文关键词：Serious games analytics,Pattern mining,Learning behavior,Learning process,Problem-solving,Middle school science
论文评审过程：Received 30 April 2016, Revised 22 September 2016, Accepted 30 September 2016, Available online 3 November 2016, Version of Record 26 April 2017.
论文官网地址：https://doi.org/10.1016/j.chb.2016.09.062
