Data help for five PhD research teams in one course

In Spring 2026 a course in the Interdepartmental PhD Program in Neuroscience asked its students to find existing data to ask questions about STEM and K-12 education, and to present posters in May. The course sent its student teams to the DataSquad for help finding data and analyzing it.

The teams’ questions included whether inequality and government education spending predict learning gaps across socioeconomic groups in the PISA 2022 dataset, whether English language learner status affects California students’ science test scores, how to design a survey to study flipped classrooms in community colleges, and whether students with ADHD respond differently to reward-based learning tasks in an open dataset from OpenNeuro.

For each team, DataSquad members used library resources and outside sources to identify data, then met to choose a statistical approach that could actually answer the question. Where a team had no data yet, the help was survey design: what to ask, how to reach people, and how much data would be enough.

It is one of the squad’s clearest teaching roles. The students leave with a poster, and the squad members leave having explained statistics to people from another field.