Applying Learning Engineering and Learning Analytics to Design Prototype Online Courses on a Lifelong Learning Platform: The LEAF-5 Framework
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Abstract
Thai universities have invested heavily in learning management systems, yet most online courses are still designed one at a time, with no shared template instructors can reuse. This article proposes LEAF-5, a component-based learning-engineering framework for prototype online courses on an institutional Lifelong Learning Platform. LEAF-5 integrates ADDIE with learning analytics. It organises five components (learning units, instructional media, learning activities, automated formative assessment, and learning analytics) into three layers: content, interaction, and data. The components are grounded in theories central to computing education: computational thinking, constructionism, cognitive load, constructive alignment, and self-regulated learning. A central design decision is that the framework runs only on standard tools the institution already owns, so adoption needs no special infrastructure; assessment is tied to objectives through constructive alignment, and analytics are treated as design feedback rather than causal proof of learning. The framework was empirically validated on the NRRU3L platform. This article abstracts the reusable design logic for other institutions.
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