Abstract
The focus on assessment of learning experiences has shifted from knowledge to competences. Unfortunately, assessing certain competences is mainly a subjective task, being problematic for both the evaluators and the evaluated. Additionally, when the learning process is computer-supported and the number of students increases, traditional assessment procedures suffer from scalability problems. In this paper we propose a query language that supports grading learning competences according to students’ performance in an online course. Using it we automatically extract different objective indicators about students work in a Learning Management System (LMS). Evaluators can use this computer programming-like language to express a number of required indicators. Such indicators are automatically obtained from the activity logs generated by the LMS.
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Balderas, A., Ruiz-Rube, I., Dodero, J.M., Palomo-Duarte, M., Berns, A. (2013). A Generative Computer Language to Customize Online Learning Assessments. In: Hernández-Leo, D., Ley, T., Klamma, R., Harrer, A. (eds) Scaling up Learning for Sustained Impact. EC-TEL 2013. Lecture Notes in Computer Science, vol 8095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40814-4_66
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DOI: https://doi.org/10.1007/978-3-642-40814-4_66
Publisher Name: Springer, Berlin, Heidelberg
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