Work

Measuring and Visualizing Students’ Behavioral Engagement in Writing Activities

Year: 2014

Type: article

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.

Source: IEEE Transactions on Learning Technologies

DOI: 10.1109/tlt.2014.2378786

Authors: Ming Liu, Rafael A. Calvo, Abelardo Pardo, Andrew Martin

Institutions: Southwest University, The University of Sydney, Young and Well Cooperative Research Centre, UNSW Sydney

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: bronze

Funders: Chongqing Social Science Planning Fund, Fundamental Research Funds for the Central Universities, Young and Well Cooperative Research Centre