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
Link To Document :
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