Campus Analytics

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.

Want to try it out?

Analytique du campus

La science des données au service de l’éducation. Notre objectif est d’utiliser la puissance de l’apprentissage automatique et de la science des données pour découvrir des modèles et des chemins cachés dans le système éducatif de l’EPFL.

Campus Analytics est une initiative du Center for Digital Education créée dans le but de fédérer la recherche scientifique et institutionnelle de l’EPFL, notamment en ce qui concerne les données académiques.

L’objectif de ce projet est de collecter et d’enrichir des données pédagogiques à l’EPFL, et de les analyser grâce à l’utilisation de techniques de data science et de machine learning.

L’application des principes de la science des données aux données académiques collectées à l’EPFL peut révéler des secrets et fournir des informations qui seraient autrement cachées à une observation normale.

Il peut montrer comment les étudiants utilisent différentes stratégies d’apprentissage pour atteindre un objectif commun, comment un cours spécifique amène les étudiants à abandonner, comment un choix spécifique de cours peut conduire à des résultats meilleurs ou pires dans les futurs cours, comment les parcours d’apprentissage mènent à des carrières différentes et dans quelle mesure l’orientation générale du cursus de l’EPFL est adaptée à la réalité actuelle du monde académique et de l’entreprise.

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Campus Analytics

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.

Want to try it out?