12th July 2017 in London at CodeNode

There are 78 other SkillsCasts available from FullStack 2017 - the conference on JavaScript, Node & Internet of Things

Please log in to watch this conference skillscast.

644689809 640

In this talk, Philipp Burckhardt will demonstrate how the Heinz College at Carnegie Mellon University monitors user behavior in an e-learning environment. Built on Node.js, React and Electron, the ISLE (Interactive Statistics Learning Environment) project, which is built as a part of his PhD thesis, aims at providing students with explorable lessons on statistical concepts.

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.

YOU MAY ALSO LIKE:

Monitoring and Analyzing User Behaviour - Intermediate

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.

SkillsCast

Please log in to watch this conference skillscast.

644689809 640

In this talk, Philipp Burckhardt will demonstrate how the Heinz College at Carnegie Mellon University monitors user behavior in an e-learning environment. Built on Node.js, React and Electron, the ISLE (Interactive Statistics Learning Environment) project, which is built as a part of his PhD thesis, aims at providing students with explorable lessons on statistical concepts.

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.

YOU MAY ALSO LIKE:

About the Speaker

Monitoring and Analyzing User Behaviour - Intermediate

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.

Photos