Adaptive Support for Acquisition of Self-Direction Skills using Learning and Health Data

For the 21st century learner, developing self-direction skill is crucial for both academic activities and maintaining one's healthy lifestyle. While there are technology supports for specific self-regulated learning tasks and health monitoring, research is limited on how to support development of meta-skill of self-direction process itself. In our work, we focus on designing seamless technology infrastructure to foster self-directedness of learners. We consider learning and physical activities data as a context and DAPER (data collection-analyze-plan-execution monitoring-reflect), as a data-driven self-direction skill execution and acquisition model. We bridge Learning Analytics and Quantified-Self approaches to develop the GOAL (Goal Oriented Active Learner) system to support synchronize-visualize-analyze multisource data regarding learners' learning and physical activities. This paper proposes a measurement rubric as a basis of adaptive scaffolding for skill development during the process.