Data science for education. We aim at using the power of machine learning and data science to uncover hidden patterns and paths in EPFL’s educational system.
Campus Analytics is an initiative of the Center for Digital Education created with the aim of federating the scientific and institutional research of EPFL, in particular with regard to academic data.
The objective of this project is to collect and enrich educational data at EPFL, and analyse it through the use of data science and machine learning techniques.
Applying data science principles to EPFL academic data can unlock secrets and provide insights that would otherwise be concealed from normal observation.
It can show how students use different learning strategies to reach a common goal, how a specific lecture is causing students to dropout of a course, how a specific choice of courses can lead to better or worse results in future courses, how learning paths lead to different careers, and how well the general focus of the EPFL curriculum is adapted to the current reality of the academic and business worlds.
These are all questions that affect decision-making at EPFL, whether it’s decisions taken by students, professors, or policy makers.
Our goal is to have at least some of these decisions be informed by data, by leveraging the research and brainpower from our research labs.