Exploring Data Visualization as an Emerging Analytic Technique PROCEEDING
Min Liu, University of Texas at Austin, United States ; Jina Kang, Pan Zilong, Wenting Zou, Hyeyeon Lee, Univ. of Texas at Austin, United States
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Vancouver, British Columbia, Canada ISBN 978-1-939797-31-5 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA
Visual analytics have emerged as a way to allow researchers to understand big data in diverse learning contexts We are interested in using visualization techniques to examine learners’ behavior patterns in an adaptive learning environment and explore the relationship between performance and behavior patterns Participants were first-year students entering into a pharmacy professional degree program As part of a large research effort, in this study we focused on high and low performing students The findings showed the visualizations confirmed some findings of the statisitical analyses and at the same time revealed the nuanced interesting findings that can be missed otherwise Combining with traditional statistical analyses with visualization techniques has provided a more detailed picture of learners’ behaviors in an adaptive learning envuronment Such research should provide useful insights about using analytics to understand how learners use an adaptive learning system
Liu, M., Kang, J., Zilong, P., Zou, W. & Lee, H. (2017). Exploring Data Visualization as an Emerging Analytic Technique. In J. Dron & S. Mishra (Eds.), Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1681-1690). Vancouver, British Columbia, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved August 21, 2018 from https://www.learntechlib.org/primary/p/181326/.
© 2017 Association for the Advancement of Computing in Education (AACE)
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