Applying lag sequential analysis to detect visual behavioral patterns of online learning activities
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Date
2010-03-01
Authors
Hou, H. T.
Chang, K. E.
Sung, Y. T.
Journal Title
Journal ISSN
Volume Title
Publisher
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.