Applying lag sequential analysis to detect visual behavioural patterns of online learning activities

A study was conducted to make an empirical observation and apply sequential analysis to detect learners' behavioral patterns. The participants in this study were 43 3rd-year students majoring in information management at a college of technology in Taipei. Six online learning activities were explored including information sharing, viewing peerwork, providing feedback, e-note taking, and proposing and answering questions. After giving the lectures, the teacher asked the students to conduct these six online learning activities from May to mid-June 2005. Each operation conducted by students in the system during the activities was coded and recorded automatically based on their sequence. The behavioral transfer diagram was then inferred by lag sequential analysis. The behavioral pattern indicates that D was almost independent from all other learning activities, and there were no sequential correlations between FBN, QS and D.