Announcing a Hackathon – Dashboard Building Learning Analytics – February 16th & 17th

Location: Belle van Zuylenzaal, Singel 425, Amsterdam
Dates: 16th & 17th February – 2015
Start time 10 AM.

To enroll please fill in the following form (costs 1 minute):

Space for 30 participants in room. Possible to work through the Internet.

Description: This is a hackathon to explore Learning Analytics dashboard building. Mockups, requirement gathering followed by client side (JavaScript) programming against standards based web web services backed against fake user data.

In the results-oriented context of modern higher education, growing concerns among both students and educators are those of quantifiability and efficacy. How, in other words, can the experience of higher education be objectively measured? Based on such measurements, how well does higher education “work”?

The University of Amsterdam is committed to developing systems to furnish answers to these questions. And as stakeholders in the quality of the education we provide, who better to help achieve this goal than you – the students? We invite anyone with a an understanding of programming to attend the upcoming Learning Analytics Hackathon. You are also welcome for the first half day to brainstorm over requirements.

Over the course of two days, you will organize into small teams, familiarize yourself with the requirements (both abstract and functional) of a learning analytics application, design a (paper-based) mockup for an application of your own, and (start to) implement it using HTML5, CSS and JavaScript. The final product will be a learning analytics “dashboard”: a small, interactive program that fetches learning data and visualizes it in a useful way. (You might, for instance, design a dynamic timeline to show all the assignments submitted to Blackboard by a group of students.)

Ethics and Privacy are of course, a central concern in the context of learning analytics: if a student’s learning experience is to be recorded, the resulting data should also be secure and used with well  informed consent. For this reason, you will be working to visualize the data of randomly-generated, fake students. You may also visualize a data set of your own choosing.

We will arrange for a comfortable environment, opportunities for teams to give and receive feedback on each others’ designs, and engaging guest speakers. 

For further contact please send an e-mail to:

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