Discovering the two-step lag behavioral patterns of learners in the college SPOC platform

Zhi Liu, Hercy N.H. Cheng, Sanya Liu, Jianwen Sun

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Due to high retention rates, small private online course (SPOC) has become increasingly popular among universities. However, existing analyses of learning behavioral patterns in SPOC remain extremely lacking. This present study conducts an empirical analysis on the behavioral patterns of 12,517 undergraduates engaging in a college's SPOC platform, called StarC. In this study, the authors collected and summarized the learning behaviors generated from these learners during 348 days of observation. They further coded the behaviors and extracted the two-step lag sequences in learning processes of individuals. The frequency analysis and sequential analysis were subsequently adopted to discover the distributions and frequency transition patterns of the two-step behavioral sequence in StarC. Besides, grade similarities and differences were computed and analyzed in terms of behavioral patterns. With these results, the potential and inadequacies of the learning platform are discussed, and some suggestions are offered for future work on the study and development of SPOCs.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalInternational Journal of Information and Communication Technology Education
Issue number1
Publication statusPublished - Jan 1 2017
Externally publishedYes


  • Learning Behavior
  • Small Private Online Courses (SPOCs)
  • Transition Sequences
  • Two-Step Sequential Analysis

ASJC Scopus subject areas

  • Education
  • Computer Science Applications


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