K-12 Learning Analytics

This research project investigates the learning analytics adoption and implementation processes in K-12 schools. A pilot study (completed May 2018) indicates that while there is significant investment in educational technology and a growing data culture, most schools do not fully realize or have the capacity to employ the large volumes of generated data to develop actionable, personalized learning for students that could improve educational outcomes. Effective use could help to break down siloed systems, promote interoperability, and broaden, deepen, and contextualize datasets that are available to various stakeholders. Additionally, the study found that companies drive most educational technology implementations in schools and educators do not fully understand their capabilities. High-costs, minimalist standards, and a lack of transparency, coupled with insufficient training for new technologies, can reduce stakeholder buy-in and squander public or philanthropic funding for schools. The goal of this project is to develop a research-informed model that can help schools identify needs specific to their context, remove barriers to adoption, reduce overall costs, and ultimately, improve student outcomes. Researchers:
Dr. George Siemens
Justin Dellinger
Dr. Ryan Baker