DocumentCode
82974
Title
Measuring and Visualizing Students’ Behavioral Engagement in Writing Activities
Author
Ming Liu ; Calvo, Rafael A. ; Pardo, Abelardo ; Martin, Andrew
Author_Institution
Sch. of Comput. & Inf. Sci., Southwest Univ., Chongqing, China
Volume
8
Issue
2
fYear
2015
fDate
April-June 1 2015
Firstpage
215
Lastpage
224
Abstract
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.
Keywords
behavioural sciences computing; cloud computing; computer aided instruction; data visualisation; Tracer; cloud-based application; controlled one-hour writing session; document development; learning activities; learning analytic system; student behavioral engagement measures; student behavioral pattern visualization; Atmospheric measurements; Clustering algorithms; Context; Data visualization; Educational institutions; Particle measurements; Writing; Computers and Education; E-Learning Tools; E-learning tools; Learning Analytics and Writing Assessment; Visualization; computers and education; visualization;
fLanguage
English
Journal_Title
Learning Technologies, IEEE Transactions on
Publisher
ieee
ISSN
1939-1382
Type
jour
DOI
10.1109/TLT.2014.2378786
Filename
6979251
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