Data Science is one of the best skillsets you can develop in order to pursue a successful career. Choose a project in the field of education for a better society.
The following demos were produced by students working with us for their semester projects. We routinely show these to the EPFL administration, such as the vice-president for education.
We build the datastore and the methods for learning analytics to enhance teaching and learning at EPFL. Do you want to apply data science to education ? We are looking forward for your contribution.
Campus Analytics is an initiative of the Center for Digital Education (CEDE) of Dr. Patrick Jermann and the Computer-Human Interaction in Learning and Instruction Lab (CHILI) of Prof. Pierre Dillenbourg, created with the goal of bringing together scientific and institutional research at EPFL.
The EPFL leadership is committed to transform our university into a world leader in the domain of data science. Indeed, a considerable number of research labs at the university rely on big data and machine learning techniques to conduct ever more innovative research, in domains ranging from neuroscience to social media mining.
Yet, such an ambitious goal can not be complete without the application of data science principles to the functioning of our own university, our teachers, and our students. The amount of educational data that is available today, especially since the advent of MOOCs, and with the strong online presence of the current students’ generation, has reached an order of magnitude that allows it to be called “big data”. And where “big data” exists, so does machine learning and data visualisation (not just excel charts, but also scientific visualisation).
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 in our research labs.
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