The Education Data Science (EDS) MS program aims to train analysts and researchers to become experts on individual and collective teaching and learning and to study digital forms of these data present in many organizations today. When studying these data, a broad set of goals comes to mind: Equity, efficacy, engagement, fulfillment, creativity, cognitive depth, and more.
An important element of the EDS MS program is completing research projects. We seek external collaborators who have organizational questions, challenging data needs, and shareable datasets for eager students to analyze and contribute to addressing.
More about the Education Data Science program
EDS MS students are well-trained to conduct education data science research. Students join the program with a solid set of quantitative skills, as many students have completed undergraduate degrees in relevant STEM fields or have acquired valuable work experience before they join EDS.
By the time students start working on their Capstone Projects, they have an additional year of coursework completed. Students are required to take foundational courses in statistics, data processing, and machine learning. Additionally, they complete at least two courses in three out of five data science specializations (Natural Language Processing, Causal Methods, Network Science, Measurement, and Learning Analytics). In addition, students take coursework on substantive education topics, such as higher education, early childhood development, education policy, or the learning sciences.
We understand that research projects require sufficient scaffolding and support and that having students work with your organization’s data can be time-consuming. Therefore, we provide several resources to guide students throughout the research process. Besides that students’ coursework should support their research projects, students are required to take a dedicated course for their Seminar and Capstone Project. This course structures and facilitates their ongoing work through weekly planning, reflection, and peer review activities. In addition, all students will be assigned a faculty mentor.
What are we looking for?
We are seeking data that are challenging, yet manageable for individuals or pairs of students to complete with about ~8 hours a week of work.
EDS MS students are interested in a variety of topics, ranging from early childhood education, workforce learning, equity in education, and assessment. We are looking for data that concern processes of individual and collective learning. This can vary from school district records or Zoom feeds for districts during COVID; detailed information from online courses and their contents and interactions; information on employee (re)training modules and their efficacy; team formation efforts and their returns; Stackoverflow threads; consensus formation in deliberative groups; and much more.
There are two types of research projects EDS students work on
Seminar Projects
Seminar Projects are team-based projects that EDS students work on during their first year. This project takes ~12 weeks. We will provide our students with a few projects to choose from (research question and dataset) and guide them through completing the research question through structured assignments.
We are looking for external collaborators who have a focused question and a dataset that students can explore. Each year, we explore potential collaborations starting in August.
Capstone Projects
Capstone Projects are the final EDS project and students will work more independently on this project from Fall to Spring (~30 weeks) during their second year. A Capstone Project is supported by coursework and a faculty supervisor.
The project is more ambitious and less structured by assignments compared to the Seminar
Project. Students must develop their own research question and are responsible for developing the
research analysis plan and timeline.
We are looking for external collaborators who have more open-ended questions and challenging data needs. Each year, we explore potential collaborations starting in May.
Interested in collaborating?
Colalboration partners have been secured for the 2024-2025 academic year Seminar Projects and Capstone Projects.
If you are an education or education technology organization interested in collaborating and sharing your data set in the future, please contact Sanne Smith, Program Director the Education Data Science MS Degree, in the open application period (May-August 2025).
Data Privacy
Learner and teacher data are often sensitive and sharing these data requires thoughtful care. We are set up to work with you in developing a Data Use Agreement through the Stanford Office for Sponsored Research. In addition, capstone projects may require IRB approval if the data contain code or links that could identify individuals. Lastly, Stanford has services and resources to support the safe use of moderate and high-risk data.