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Philipp Burckhardt will share insights obtained in the process of developing a session logging system that tracks every click and every action of a given student. From weighing the pros and cons of using cookies, local storage or server-side storage to deciding upon whether to store the collected data in a SQL database or document store, he will reflect on the decisions made and the lessons learned.
Gathering data is only the first step, though. Analyzing the data is a much more difficult undertaking. Since collected data does not lend itself to a simple spreadsheet format but consists of time stamps, unstructured text and the like, cleaning and molding the data into an appropriate format is a delicate task. Join Philipp as he elaborates on the development of an online dashboard allowing professors to visualize the collected data, view summary statistics, and apply advanced machine-learning methods to predict future student behaviour and outcomes.
Find out more at www.isledocs.com.
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Philipp Burckhardt
Philipp Burckhardt is a PhD Student in the joint Statistics & Public Policy program of the Department of Statistics and the Heinz College at Carnegie Mellon University. He hold a Master's degree in Applied Statistics from the University of Oxford and a Bachelor's degree in Economics from Humboldt-University. Some of his interests are the development of statistical methods for analyzing unstructured textual data, specifically from the health-care domain and to develop platform-independent and browser-enabled statistical tools, to aid decision-making and make it easier to turn insights into action. Recently, he has become a major contributor to the Node.js JavaScript ecosystem, having (co)-authored more than 200 npm packages in the areas of numerical computing, statistical tools and text mining, among others. For his dissertation, he is working on an e-learning platform for statistics education built on state-of-the-art web technologies. Together with Athan Reines, he is engaged in the development of a standard library for JavaScript called stdlib. He has spoken at various international conferences on topics ranging from political science, health-care informatics to machine learning and software engineering.