Data-driven instruction involves collecting information about students and using that information to enhance the learning experience. This instructional model accounts for all students’ needs, abilities and comprehension levels. The three steps in this model are: 1) data collection, which is done through assessments, 2) data analysis, which is completed by reviewing patterns and 3) action, where instructors decide whether to move on to another topic based on what their students do or don’t know.
Data-driven instruction refers to tailoring course delivery in a way that meets the needs of every student. Professors will regularly collect formative data—throughout a learning unit—and summative data—collected at the end of a learning period. They will then use this information to decide what unit comes next in instruction.