Data Science Methods for Digital Learning Platforms

In this 16-week program, participants will learn to conduct analysis on real-world data, working directly with authentic student interaction data that has not been cleaned. You’ll compare statistical and psychometric approaches to machine learning and data mining methods. You will also learn how to move beyond the well-structured use cases often utilized in introductory data science and statistics courses, which are often not representative of the data that comes from digital learning platforms. The program is online and asynchronous, with one optional synchronous and virtual “ask me anything” session with the instructors. Each module includes discussion-based interactions with peers and instructors and a project-based assignment for which fellows will be able to apply the skills they learn using authentic tools and datasets. The examples and assignments corresponding with each module will align with real challenges and scenarios common to digital learning platforms. Emphasis is given to identifying the development of relevant research questions and understanding the limitations and affordances that different types of digital learning platform data may provide in addressing these questions.