Teaching the Data and History Course

For the last few years, I have been teaching a course called Data and History in which students use AI for coding, statistics, and mapping. Students move at a pace that would have been impossible before AI, when the syntax of statistical programming would have bogged them down. Instead, students focus on critical thinking about data and history. Students make and analyze real-world data sets, from OCR’d business records to historical surveys. They learn to clean real-world messy data, developing skills that are not taught in math or CS courses. By combining visualization techniques with quantitative reasoning, students reveal patterns, correlations, and structural changes that no single document could show. At the same time, the course historicizes data itself, examining how categories, surveys, and statistics were constructed and shaped by power. Students leave not only able to interpret arguments about numbers, but to use numbers responsibly to make original arguments.