This poster explores how to develop a working framework for STEM education that uses both human annotated and ma- chine data across a purpose-built learning environment. Our dual approach is to develop a robust framework for analysis and investigate how to design a learning analytics system to support hands-on engineering design tasks. Data from the first user tests are presented along with the framework for discussion.