Analytics for learning design: A layered framework and tools.

• Autores: Davinia Hernández-Leo, Roberto Martinez-Maldonado, Abelardo Pardo, Juan A. Muñoz‐Cristóbal, María Jesús Rodríguez Triana
• Localización: British journal of educational technology, ISSN 0007-1013, Vol. 50, Nº. 1, 2019, págs. 139-152
• Idioma: inglés
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• Dialnet Métricas: 3 Citas
• Resumen

  • The field of learning design studies how to support teachers in devising suitable activities for their students to learn. The field of learning analytics explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and fragmented work exploring the active role that data analytics can play in supporting design for learning. This paper builds on previous research to propose a framework (analytics layers for learning design) that articulates three layers of data analytics—learning analytics, design analytics and community analytics—to support informed decision‐making in learning design. Additionally, a set of tools and experiences are described to illustrate how the different data analytics perspectives proposed by the framework can support learning design processes. [ABSTRACT FROM AUTHOR]