Reward points calculation based on sequential pattern analysis in an educational mobile app

In recent years, learning on smartphones has becomes a significant trend in education. The educational mobile app, Practi, provides a platform that can let students practice their knowledge of math and science. Practi gives students reward points when they finish a course or solve a question to encourage them to keep using the app. Students can use these reward points to redeem in-app items. However, a pre-defined amount of reward points does not always fit every student's situation. For instances, when most of students feel the question is difficult, the students who solve the question easily may be given more rewards. On the other hand, when a student achieves mastery in the required skills of a particular course or set of questions, he or she should be awarded more points. In order to make Practi capable of giving proper reward points according to students' questionsolving behaviours, this research designs an Apriori based algorithm that can extract students' behaviours patterns and give students appropriate reward points according to the result of pattern comparisons.