Issue No. 02 - April-June (2015 vol. 8)
Ming Liu , School of Computer and Information Science, Southwest University, Chongqing, China
Rafael A. Calvo , School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia
Abelardo Pardo , School of Electrical and Information Engineering, The University of Sydney, Australia
Andrew Martin , School of Education, University of New South Wales, Sydney, NSW, Australia
Engagement is critical to the success of learning activities such as writing, and can be promoted with appropriate feedback. Current engagement measures rely mostly on data collected by observers or self-reported by the participants. In this paper, we describe a learning analytic system called Tracer, which derives behavioral engagement measures and creates visualizations of behavioral patterns of students writing on a cloud-based application. The tool records the intermediate stages of document development and uses this data to measure learners' behavioral engagement and derive three visualizations. Writers (N= 23 University students) participated in a controlled one-hour writing session in which they post-facto self-reported their level of behavioral engagement. Results show that the level of behavioral engagement automatically estimated by the system correlates with the level reported by the participants. Additionally, users stated that the visualizations were coherent with their writing activity and were useful to help them reflect on the writing process.
Writing, Data visualization, Educational institutions, Clustering algorithms, Atmospheric measurements, Particle measurements, Context
M. Liu, R. A. Calvo, A. Pardo and A. Martin, "Measuring and Visualizing Students’ Behavioral Engagement in Writing Activities," in IEEE Transactions on Learning Technologies, vol. 8, no. 2, pp. 215-224, 2015.