Designing Theory-Driven Analytics-Enhanced Self-Regulated Learning Applications

There is an increased interest in the application of learning analytics (LA) to promote self-regulated (SRL). A variety LA dashboards and indicators were proposed support different crucial SRL processes, such as planning, awareness, self-reflection, self-monitoring, feedback. However, design these often without reference theories science, human-computer interaction (HCI), information visualization (InfoVis). Moreover, there a lack theoretically sound frameworks guide systematic development scaffold SRL. This chapter seeks explore theoretical underpinnings LA-enhanced applications, drawing from fields HCI, InfoVis. We first present Student-Centered Learning Analytics-enhanced Self-Regulated (SCLA-SRL) methodology for building theory-driven applications with learners. then put this into practice by designing developing novice programmers' higher education context.