Research into learning analytics focuses on how to combine, monitor, and use the data being collected by IT systems to better support student learning. With so much information being collected about which resources students are accessing, where they are accessing them from, and where the potential hazards along their learning journies are, one goal of a learning analytics system is to be able to predict learning obstacles and recommend solutions before the hazards become insurmountable. On the other end, learning analytics systems offer a way to match course content and activities to student's immediate needs so students encounter less redundancy, more relevance, and can accelerate their learning trajectories.
With a powerful learning analytics system running in the background, CRADLE researchers are incorporating that data and analysis into the creation of e-Learning courses, activities and visualizations. Current projects look at ways of enhancing student feedback, peer reviewing, and expert modeling systems so students can better understand, reflect upon, and apply what they are learning.