Co-Principal Investigators: Chen, Bodong; Botelho, Anthony; Roschelle, Jeremy; Pautz Stephenson, Stefani

The use of digital learning platforms has grown considerably in recent years. These platforms generate considerable amounts of process data, which show how users are interacting with the content. However, many in the education research community struggle to analyze and extract meaningful knowledge from large-scale process data to inform education practice or policy. This training program will provide education researchers with training on how to effectively apply various algorithms to leverage big data from digital learning platforms. The training team will deliver content within a framework for advancing humanistic and equity-oriented data analysis.  The training is intended for education researchers in academia, industry, non-profits, school districts, and government who have intermediate-level statistics or psychometrics experience.

The training team will recruit 3 cohorts with 20 to 50 participants (approximately 220 participants in total) to engage in a 4-month-long virtual training program. The training format will be module-based instruction with 17 weekly asynchronous tutorials, discussion forums, and synchronous discussions with instructors to build foundational data science skills during the training. The training team also will develop a fully open-access website and YouTube channel to host materials from the training for both participants and non-participants looking to extend their data analysis skills.