Education Studies 140 - Discovering Data

Data plays a central role in shaping education research, policy, and practice. However, despite the frequent use of quantitative data in education research, students are often expected to engage with data in advanced ways without first having a structured opportunity to develop their foundational skills. Intended for students with no prior experience in programming or statistics, this course will introduce students to the data exploration, visualization, and analysis skills commonly applied to quantitative educational data. The course will build students’ data literacy via a practical overview of methodological topics, including the collection, organization, and interpretation of educational data. It will also explore the theories and frameworks which underpin these methods in order to highlight how educational data can be used (and misused) in real-world scenarios. The course will begin with a practical introduction to statistical programming, data manipulation, and data visualization with the R programming language. Experimental design, data analysis, and communication of research results will be emphasized through a combination of lectures, discussions, case-studies, and hands-on work with authentic educational datasets. This course will prepare students to thoughtfully and ethically collect, analyze, interpret, and communicate quantitative information to the diverse range of audiences relevant to education research.

Limited to 18 students. Fall Semester. Prof. Rosenthal

How to handle overenrollment: Priority to first years, then Education Studies majors, then according to seniority (sophomores, then juniors, then seniors), then random selection.

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: Quantitative reasoning, group work, oral presentations, and discussions.