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A Domain Specific Language for Online Learning Competence Assessments

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URI: http://hdl.handle.net/10498/33357

ISSN: 0949-149X

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Author/s
Balderas Alberico, AntonioAuthority UCA; Dodero Beardo, Juan ManuelAuthority UCA; Palomo Duarte, ManuelAuthority UCA; Ruiz Rube, IvánAuthority UCA
Date
2015-05
Department
Ingeniería Informática
Source
International Journal of Engineering Education - 2015, Vol. 31 n.3, pp. 851-862
Abstract
Learning outcomes in higher education are defined as competencies, which are either specific or generic. The former refers to those skills specific to the subject studied. The latter, also known as transferable skills, refer to other capabilities that a capable professional has to put into practice to work in real-world. Generic competencies are usually shared amongst most science fields, and include teamwork, leadership and self-criticism. These skills are inherently difficult to assess, as they are not usually considered in traditional engineering assessment procedures. As a result, lectures usually have to assess them using subjective information. This is especially problematic when the number of students increases. In this paper, we introduce Simple Assessment-Specific Query Language (SASQL), a Domain Specific Language (DSL) to alleviate this issue. It is a formal language that can be automatically processed to execute SASQL sentences using an assessment-specific vocabulary. SASQL has a simple syntax, oriented to learning assessments. Using our proposed workflow, a course coordinator can extract different objective indicators to assess competencies defined in the syllabus using simple queries. Such indicators are automatically extracted from the activity logs generated by the Learning Management System (LMS). Two case studies with Moodle LMS-based courses are carried out to explain how such indicators can be obtained and how to interpret the results obtained for student assessments.
Subjects
online learning; competence assessment; technological support in online education; domain-specific languages; learning analytics
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional

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