Learning behavior analysis and prediction based on e-learning platform data

With the rapid development of the online education, various E-learning platform have generated tremendous amount of data, which provide the basis for quantitative analysis of learning behavior. The purpose of this study was to investigate the relationship between students characteristic and online learning behavior. Based on the learning data from the courses offered by Chongqing E-learning Academy for Leadership platform, this study analyzed the differences of cadres' learning behavior from nine aspects: learners' age, gender, rank, unit, login times, studying times, learning completion, the correlation of the gender and rank between with the elective course, and the correlation of the age and rank between with the elective course. The results showed that the login times and the learning times are related with the month, the completion rate is related with the units and the average number of elective courses are relate with the gender and rank.