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A Multilevel Framework and Method for Learning Analytics Integrated Learning Design
Author(s) -
Nancy Law,
Leming Liang
Publication year - 2020
Publication title -
journal of learning analytics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.084
H-Index - 7
ISSN - 1929-7750
DOI - 10.18608/jla.2020.73.8
Subject(s) - learning analytics , operationalization , computer science , learning sciences , educational technology , analytics , instructional design , curriculum , learning design , knowledge management , data science , mathematics education , multimedia , psychology , pedagogy , philosophy , epistemology
Efforts to realize the potential of learning analytics (LA) to contribute to improving student learning and learning design have brought important advances. A review of successful cases of learning analytics applications reveals that 1) there is a tight coupling between the learning outcome (LO) goals, task sequence design, and the learning analytics and feedback in each case, and 2) the learning analytics to be deployed and the feedback to be provided to learners and/or teachers are integral to the learning design (LD) rather than constructed after the LD is completed. Learning design frameworks in the literature have focused on generic learning task taxonomies and are unable to scaffold LA-integrated LD practice. This paper proposes a multilevel framework for LA-integrated LD, which provides a hierarchically nested multilevel structure for the design of LD and LA elements based on 60 STEM curriculum units collected from authentic classrooms. The framework includes a design process model in the form of a Learning Design Triangle and the concept of Learning Analytics integrated Curriculum Component Design Patterns (LA-CCDP). Operationalization of the framework is illustrated using one STEM curriculum unit. This framework can be adopted for professional learning and technology development to support LA-integrated LD practices.

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