As a result of next-generation networking and the Internet of Things (IoT) technologies, big data analysis is possible and has been shown to have a positive impact on areas of national significance yet requires new tools to deal with the variety and quantity of data multiplying at an exponential rate.. Concurrently, IoT technologies are rapidly becoming a mainstream data source. Training simulations have historically been limited either to computer-based simulations or live human-observable field-based simulations ;however, IoT technologies can open up innovative, hybrid digital-physical opportunities both for delivering and for understanding the outcomes of training in a much more dynamic and comprehensive way. The feasibility of IoT technologies in training has historically been limited by interoperability and scale. However, Advanced Distributed Learning’s Experience Application Programming Interface (xAPI) allows interoperability and scale in next-generation training environments and provides a way to standardize the formative data of human experience captured through digital context. It also provides a way to capture information and formalize human experience from multiple and varied networked devices into standardized, human-readable statements. These can inform both human and machine learning through leveraging big data analysis and interoperability of the IoT technologies. By leveraging the xAPI and IoT technologies as a cyberphysical system embedded in virtual and live training scenarios, it is possible to capture and measure real-time team performance for immediate analysis and remediation or for post hoc analysis in after action reviews. This paper discusses the application of learning analytics and design for an IoT context through describing the implementation of 1) a live action medical simulation as part of the Global Smart Cities Challenge (sponsored by the NIST and the OSTP) and 2) the proposed capture and analysis of communication performance data and measures within specific coalition training scenarios supporting the 2015 Bold Quest Assessment sponsored by the Joint Fires Division of the Joint Staff.