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Analytics for learning design: A layered framework and tools
Author(s) -
HernándezLeo Davinia,
MartinezMaldonado Roberto,
Pardo Abelardo,
MuñozCristóbal Juan A.,
RodríguezTriana María J.
Publication year - 2019
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/bjet.12645
Subject(s) - learning analytics , analytics , computer science , data science , software analytics , data analysis , field (mathematics) , cultural analytics , set (abstract data type) , instructional design , business analytics , knowledge management , semantic analytics , world wide web , multimedia , data mining , software , software construction , mathematics , business model , marketing , software system , web service , pure mathematics , data web , business , business analysis , programming language
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.