高校SPOC环境下学习者行为序列的差异性分析研究

Analyses of Differences on Learners’ Behavioral Sequences in a College’s SPOC Environment

Due to the flexibility in the way of teaching and controllability of learning， small private online courses (SPOCs) have become increasingly popular among universities. However， existing analyses of learning behavioral patterns in the course resource module of SPOCs remain extremely lacking. This current study is an empirical observation and analysis of the behavioral patterns of 12517 undergraduates participating in the SPOCs during one academic year， called StarC developed by Central China Normal University. In this study， we recorded and summarized the learning behaviors of these participants， we further coded the behaviors and extracted the lag two-step transition sequences of participants' behaviors. The frequency analysis and two-step sequential analysis are then conducted to discover the distributions and frequency transition patterns of the two-step behavioral sequence in the SPOCs. Besides， lag sequential analysis method (LSA) was applied to discover the most significant several sequence patterns in each grade. The differences between grades in behavioral patterns were also discussed. Based on these results， we analyzed the operability， potential and limitations of the learning platform and provide suggestions for future research on the SPOCs.