Open data framework for sustainable assessment of project-based learning experiences
Identificadores
URI: http://hdl.handle.net/10498/33361
DOI: 10.1108/PROG-12-2015-0078
ISSN: 0033-0337
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2016-01-19Department
Ingeniería InformáticaSource
Program, Vol. 50 n.4 pp. 380-398, 2016Abstract
Purpose
In a project-based learning experience, the detailed monitoring of the activities in which team members participate can be useful to evaluate their work. However, the project activity produces a large amount of data that can be hardly assessed by a single project supervisor. This poses a scalability issue if the number of users or projects size increases. In this vein, the purpose of this paper is to make the assessment of online learning experiences more sustainable.
Design/methodology/approach
This paper describes a learning-oriented collaborative assessment method, supported by an open data framework. Also, an architecture for the extraction of different indicators to facilitate the assessment process is presented.
Findings
The assessment method and the open data framework were applied to a project-based course on web engineering. This experience has provided positive evidences because the grade measurement was backed up with assessment evidences and calculated with less effort.
Research limitations/implications
At the moment, results indicate that apparently there are no significant evidences against the sustainable evaluation practices for students’ summative evaluation. Nevertheless, when more data become available, a more statistically significant analysis could be made to determine the influence of the assessment practices in the final result of the evaluated skills.
Originality/value
In contrast to various existing proposals for e-assessment, the strategy focuses on assessing learning experiences in software development projects. Also, the approach is based on the reuse of information from external process supporting tools by integrating a number of metrics in a non-intrusive way.
Subjects
Metrics; Project-based learning; Extraction, transformation and load; Software forges; Sustainable assessmentCollections
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