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https://hdl.handle.net/2440/140055
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Type: | Journal article |
Title: | Analytics for learning design: A layered framework and tools |
Author: | Hernández-Leo, D. Martinez-Maldonado, R. Pardo, A. Muñoz-Cristóbal, J.A. Rodríguez-Triana, M.J. |
Citation: | British Journal of Educational Technology, 2019; 50(1):139-152 |
Publisher: | Wiley |
Issue Date: | 2019 |
ISSN: | 0007-1013 1467-8535 |
Statement of Responsibility: | Davinia Hernández-Leo, Roberto Martinez-Maldonado, Abelardo Pardo, Juan A. Muñoz-Cristóbal and María J. Rodríguez-Triana |
Abstract: | 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. |
Rights: | © 2018 British Educational Research Association |
DOI: | 10.1111/bjet.12645 |
Grant ID: | http://purl.org/au-research/grants/arc/FL100100203 |
Published version: | http://dx.doi.org/10.1111/bjet.12645 |
Appears in Collections: | Computer Science publications |
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