Critical Factors In Data Governance For Learning Analytics
| Autor: | Noureddine Elouazizi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Computer Science::Machine Learning
Knowledge management Computer science business.industry Learning analytics Data science Computer Science Applications Education Data governance Data modeling Software analytics Business analytics Analytics hot spot Business intelligence business Cultural analytics data governance |
| Zdroj: | Journal of Learning Analytics; Vol 1 No 3 (2014): Widening the Field and Sparks of the Future; 211-222 |
| ISSN: | 1929-7750 |
| Popis: | This paper identifies some of the main challenges of data governance modeling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data governance model, viz., the ownership of the learning analytics data sets, its interpretation and the enacting of decision-making on the basis of this learning analytics data. It also proposes a set of high-level requirements that are necessary for modeling data governance for learning analytics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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