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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ming Liu Calvo, R.A. Pardo, A. Martin, A. |
| Copyright Year | 2008 |
| 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. |
| Sponsorship | IEEE Computer Society |
| Starting Page | 215 |
| Ending Page | 224 |
| Page Count | 10 |
| File Size | 859595 |
| File Format | |
| ISSN | 19391382 |
| Volume Number | 8 |
| Issue Number | 2 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-04-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Writing Data visualization Educational institutions Clustering algorithms Atmospheric measurements Particle measurements Context Learning Analytics and Writing Assessment E-Learning Tools Computers and Education Visualization visualization E-learning tools computers and education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Education Engineering E-learning Computer Science Applications |
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