The boost of data in schools (e.g., assessment and observational data) requires teachers to become data literate professionals to make appropriate data-based decisions for instructional improvement. However, teachers’ data literacy often falls short. The complex combination of different types of skills (i.e., analysing and interpreting skills versus context-specific knowledge and expertise to take decisions) is a major barrier to realising the potential value of using data. Therefore, we need to increase our knowledge of how teachers interpret data sources and make sense of them for instructional decision-making. And additionally, on how teachers can learn data literacy skills. Common training methods (e.g., lecturing) fall short of providing teachers with the necessary skills to give meaning to student performance data. Interactions are vital to bringing diverse data literacy skills to the surface. This project investigates the power of interactions for data literacy learning. Different studies will (1) address the difficulties regarding the reliable and valid measurement of data literacy, (2) examine how (student) teachers process visual performance data, and (3) determine characteristics of effective interactions for data literacy learning. This research will produce fundamental insights into the mechanisms underlying teachers learning of complex skills, such as data literacy.