Communications of the ACM
Learning and Evidence Analytics Framework Bridges Research and Practice for Educational Data Science
Credit: KPG-Payless
Learning analytics (LA) as a research discipline focuses on multiple perspectives of understanding and supporting educational activities utilizing collected log data. To do so at a national and even international level, educational technology platforms that enable gathering users' interaction traces and digitally generated artifacts must store data in a standardized format. In Japan, the government initiated the GIGA School project in 2020, which installed more than nine million tablet PCs and high-speed Internet access at compulsory education institutions (elemental and middle schools). Such infrastructure enables the collection of educational data and analysis with the aim to improve educational practices in each school. With standardized data logging, it is possible to aggregate data from all schools and to generate educational Big Data that can support evidence-based policy-making and research at a national level.
LEAF is an integrated technology framework that incorporates learning analytics methods and tools and can be linked to any existing learning management systems in different institutions.
At the Learning and Educational Technology Research Unit at Kyoto University, we developed the Learning and Evidence Analytics Framework (LEAF),1 an integrated technology framework that incorporates LA methods and tools and can be linked to any existing learning management systems in different institutions. The accompanying figure provides an overview of the framework. As illustrated in the figure's Part A, teachers and learners can conduct daily educational activities and access various AI-driven services utilizing the LEAF system to enrich their learning experiences and outcomes. Teachers can upload any learning materials in PDF format on BookRoll, the e-book platform, and learners can access them through standard Web browsers on their PC or mobile devices (as shown in Part B). The learning interactions are logged using standard xAPI statements and then processed to create various data-driven services in LEAF. It is then presented to the users within BookRoll or in a learning dashboard called Log Palette.
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