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Linking assessment and learning analytics to support learning processes in higher education
Schumacher, Clara
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DOI:
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https://doi.org/10.1007/978-3-319-17727-4_166-1
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URL:
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https://link.springer.com/referenceworkentry/10.10...
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Document Type:
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Book chapter
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Year of publication:
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2020
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Book title:
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Learning, design, and technology : an international compendium of theory, research, practice, and policy
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Page range:
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1-40
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Publisher:
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Spector, J. Michael
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Place of publication:
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Cham
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Publishing house:
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Springer
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ISBN:
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978-3-319-17727-4
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Publication language:
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English
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Institution:
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Business School > Wirtschaftspädagogik, Technologiebasiertes Instruktionsdesign (Ifenthaler 2015-)
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Subject:
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370 Education
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Keywords (English):
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Assessment ; Learning analytics ; Feedback ; Higher education ; Self-regulated learning
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Abstract:
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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.
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Additional information:
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Online-Ressource --- Auf Vorlage Spector, Michael J.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
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