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A visual recommender tool in a collaborative learning experience
- Source :
- Expert Systems with Applications. 45:248-259
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- We propose a tool that visually guides the recommendation process to increase collaboration.It analyzes interactions and an influence diagram which warns about the collaboration circumstances.A visual explanation decision tree shows the collaboration circumstances which are understandable.Our tool provokes self-reflection and provokes sense making about collaboration. Collaborative learning incorporates a social component in distance education to minimize the disadvantages of studying in solitude. Frequent analysis of student interactions is required for assessing collaboration. Collaboration analytics arose as a discipline to study student interactions and to promote active participation in e-learning environments. Unfortunately, researchers have been more focused on finding methods to solve collaboration problems than on explaining the results to tutors and students. Yet if students do not understand the results of collaboration analysis methods, they will rarely follow their advice. In this paper we propose a tool that analyzes student interactions and visually explains the collaboration circumstances to provoke the self-reflection and promote the sensemaking about collaboration. The tool presents a visual explanatory decision tree that graphically highlights student collaboration circumstances and helps to understand the reasoning followed by the tool when prescribing a recommendation. An assessment of the tool has demonstrated: (1) the students collaboration circumstances showed by the tool are easy to understand and (2) the students could realize the possible actions to improve the collaboration process.
- Subjects :
- Knowledge management
Computer science
business.industry
Process (engineering)
05 social sciences
Distance education
General Engineering
Decision tree
050301 education
Collaborative learning
02 engineering and technology
Sensemaking
Computer Science Applications
Artificial Intelligence
Analytics
Component (UML)
0202 electrical engineering, electronic engineering, information engineering
Influence diagram
020201 artificial intelligence & image processing
business
0503 education
Subjects
Details
- ISSN :
- 09574174
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- Expert Systems with Applications
- Accession number :
- edsair.doi...........7d191595c7a53126b006dfe68b06c2d2