Data-driven Infrastructure for Evidence-based Education and Learning

Abstract

Current eLearning infrastructures often include a Learning Management System (LMS), various ubiquitous and classroom learning tools, Learning Record Stores (LRS) and Learning Analytics Dashboards (LAD). Applying Learning Analytics (LA) methods to process data collected within such infrastructure can support various stakeholders. Learners can reflect on learning experiences, teachers can refine their instructional practices, and researchers can study the dynamics of the teaching-learning process with it. While LA platforms gather and analyze the data, there is a lack of specific design framework to capture the technology-enhanced teaching-learning practices. We proposed the Learning Evidence Analytics Framework (LEAF) and in this paper focus on the computational support for evidence extraction and analysis in a data-driven educational scenario.