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Informing learning design through analytics: Applying network graph analysis
Author(s) -
Dirk Ifenthaler,
David Gibson,
Eva Dobozy
Publication year - 2018
Publication title -
australasian journal of educational technology
Language(s) - English
Resource type - Journals
eISSN - 1449-5554
pISSN - 1449-3098
DOI - 10.14742/ajet.3767
Subject(s) - learning analytics , computer science , analytics , instructional design , data science , graph , learning design , data analysis , human–computer interaction , machine learning , multimedia , data mining , mathematics education , theoretical computer science , psychology
Learning design has traditionally been thought of as an activity occurring prior to the presentation of a learning experience or a description of that activity. With the advent of near real-time data and new opportunities of representing the decisions and actions of learners in digital learning environments, learning designers can now apply dynamic learning analytics information on the fly in order to evaluate learner characteristics, examine learning designs, analyse the effectiveness of learning materials and tasks, adjust difficulty levels, and measure the impact of interventions and feedback. In a case study with 3550 users, the navigation sequence and network graph analysis demonstrate a potential application of learning analytics design. Implications based on the case study show that integration of analytics data into the design of learning environments is a promising approach.

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