The proliferation of sensing technology and the produced sensing-based analytics (SBA) has driven several fields in the development of tools and methods that have transformed their industries. The utilization of SBA fulfills the vision of integrating many sources of information, coming from different modalities (e.g., affective, cognitive, and embodiment), to strengthen learning systems’ capacity (e.g., adaptation, promote awareness, and reflection). The authors present a practical framework that outlines four phases that can enable learning systems to leverage on multimodal data coming from SBA. Moreover, the authors showcase the benefits of SBA through a case study and discuss how sensing integration can advance contemporary learning systems.