Linking assessment and learning analytics to support learning processes in higher education


Schumacher, Clara



DOI: https://doi.org/10.1007/978-3-319-17727-4_166-1
URL: https://link.springer.com/referenceworkentry/10.10...
Dokumenttyp: Buchkapitel
Erscheinungsjahr: 2020
Buchtitel: Learning, design, and technology : an international compendium of theory, research, practice, and policy
Seitenbereich: 1-40
Herausgeber: Spector, J. Michael
Ort der Veröffentlichung: Cham
Verlag: Springer
ISBN: 978-3-319-17727-4
Sprache der Veröffentlichung: Englisch
Einrichtung: Fakultät für Betriebswirtschaftslehre > Wirtschaftspädagogik, Technologiebasiertes Instruktionsdesign (Ifenthaler 2015-)
Fachgebiet: 370 Erziehung, Schul- und Bildungswesen
Freie Schlagwörter (Englisch): Assessment ; Learning analytics ; Feedback ; Higher education ; Self-regulated learning
Abstract: In higher education assessments are mostly used for summative purposes such as grading and certifying. Albeit, assessments are also considered to support learning processes by offering formative feedback to learners about their current performance and how to improve. Even though such feedback might enhance learners’ self-regulated learning processes, it is used infrequently due to resource constraints. In addition, the competences, skills, and knowledge that should be assessed are evermore complex. To derive valid inferences about learners’ current performance, ongoing assessments across contexts are desirable. With the advancing use of digital learning environments, learning analytics are also coming in for increasing discussion in higher education. However, learning analytics are still not sufficiently linked to learning theory and are lacking empirical evidence. Hence, the purpose of this paper is to propose how theory on assessment and related feedback can be linked to learning analytics with regard to supporting self-regulated learning. Therefore, relevant concepts of assessment, assessment design, and feedback plus current perspectives on learning analytics are introduced. Based on this theoretical foundation, a conceptual integrative framework and potential learning analytics features were derived. The framework and its implications plus further research needs are discussed and concluded.
Zusätzliche Informationen: Online-Ressource --- Auf Vorlage Spector, Michael J.




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