#1115: Effects and Mechanisms of Learning Analytics-Supported Reflective Assessment in Promoting KB Competences and Data Science Competences among Preservice Teachers

Developing data-literate citizens who can effectively use data is a critical educational goal. Knowledge Building (KB) offers a promising approach, as it engages PSTs in reflective, inquiry-driven learning supported by data. Building on prior research, this study examined the effects and mechanisms of learning analytics-supported reflective assessment (LAsRA) in enhancing preservice teachers’ (PSTs) KB and data science competences. Using a quasi-experimental design, the experimental class received LAsRA within a KB environment supported by KBDeX. Multi-methodological analyses—including content analysis, lag sequential analysis, and epistemic network analysis—showed that LAsRA significantly improved PSTs’ higher-order conceptual development, epistemic engagement, and data science skills. Mechanism analysis revealed that LAsRA fosters deeper KB and data-informed decision-making by strengthening links between metacognition and advanced discourse behaviors. These findings provide both theoretical and practical guidance for integrating learning analytics and reflective assessment in teacher education.