The Educational Data Science Graduate Certificate is designed for graduate students interested in new-often digital-data sources and analytic methods in educational contexts. While there are courses and workshops designed to enable researchers to work with digital sources of data and accompanying methods, they are not widespread. At the same time, there is growing student interest in and demand for courses that equip them to work with more complex and varied sources of data, including data from course learning management systems and social media-based professional networks for educators.
The certificate objectives include:
- Wrangling data and the tidy data format
- Introduction to data visualization
- Ethics, privacy, and justice in the context of data science
- Posing questions that can be answered using digital data sources, including data from learning management systems
- Accessing and working with structured (from databases/APIs) and unstructured (e.g., text) data
- Introduction to functional programming for preparing complex datasets
- Creating static and dynamic data visualizations using R
- Using modeling interfaces (e.g., tidymodels) for specifying a range of inferential and machine learning models
- Exploring useful and ethical applications of machine learning in education
- Estimation and inference in the context of larger datasets