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

Date
2010-03-01
Authors
Hou, H. T.
Chang, K. E.
Sung, Y. T.
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the British Educational Communications and Technology Agency
Abstract
The recent trend towardsWeb 2.0 focuses on users’ active participation and interaction via online environment (Musser, O’Reilly & the O’Reilly Radar Team, 2006), and makes educational strategies more interactive and diverse. Many teaching strategies are also integrated with online learning activities. However, this raises questions about how learners conduct these online learning behaviours and about the visual sequential behavioural patterns that they employ. These patterns may provide an important reference for teachers’ or intelligent agents’ guidance for enhancing learners’ learning. Lag sequential analysis (Bakeman & Gottman, 1997) can individually examine whether the sequential relationship between each behaviour has been achieved significantly and visualise the patterns. This study tries to conduct an empirical observation and apply sequential analysis to detect learners’ behavioural patterns. Based on our initial findings, we also provide suggestions, which are expected to promote in-depth online learning.
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