Attend a Hackathon

UBC’s Learning Analytics Hackathons offer students an opportunity to work with real learning data (either your own or anonymized data) and explore how analytics can support learning and student success. The next hackathon is coming up in the spring of 2020.


Next Hackathon: Spring 2020

Co-hosted by the Learning Analytics Project, UBC LAVA (Learning Analytics, Visual Analytics), the UBC Canvas API Community (CAPICO), and Sauder Learning Services, the Learning Analytics Hackathons provide an opportunity to work with real data, brainstorm, and then prototype or build tools to address challenges that face students.

More details to come in February 2020.

Past events

November 2019: Learning Analytics Hackathon

Download the UBC Course Calendar data here!

Event recap and video coming soon!

March 2019: Learning Analytics + Canvas API Hackathon

UBC held its fifth learning analytics hackathon on March 29 and 30, giving students experience analyzing and visualizing educational data while exploring the emerging field of learning analytics.

The two-day event kicked off with a design-thinking workshop focused on encouraging students to reflect on their experiences at UBC and the problems they’d like to tackle using data. On day two, students were offered workshops that took them through each stage of a data analytics project, learning how to extract, analyze, and visualize data in a way that would be useful to other students. Students had the option of working with their own personal data from Canvas — UBC’s online learning platform — or data from a course created specifically for the Hackathon.

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October 2018: Learning Analytics + Canvas API Hackathon

students working on laptops

UBC’s Canvas API Hackathon took place on October 27 and 28, 2018, with more than 100 students signing up to spend their weekend creating apps and dashboards for Canvas — UBC’s new online learning platform.

The Hackathon gave students the chance to learn about and explore the Canvas API (application program interface), which allows users to write programs to interact with Canvas. Over the course of the weekend, students also designed and built tools for other students using the Canvas API.

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March 2018: Learning Analytics Hackathon 3.0

Do UBC students need a Tinder-style app that “matches” them with possible research topics? How can we design tools that help students know if they’re on track to succeed in an online course? On March 10 and 11, students, researchers and instructors came together for the Learning Analytics Hackathon 3.0 to brainstorm and prototype tools to address these types of questions.

The event attracted more than 100 participants who had the chance to work with open learning data from Harvard and the Open University (UK).

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January 2017: Learning Analytics Hackathon 2.0

In January 2017, the Institute for the Scholarship of Teaching and Learning and the Learning Analytics Visual Analytics group hosted Hackathon 2.0.

The event was an opportunity for like-minded people to meet and share their passion for data analysis. The hackathon was also aimed at raising the profile and visibility of learning analytics. Learning research data can give instructors feedback about their teaching approaches and resources, and how they’re working in their classrooms. It can inform departments about why certain classes are more popular than others and thus support planning at the program level.

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October 2015: UBC’s First Learning Analytics Hackathon

In October 2015, the Learning Analytics Visual Analytics (LAVA) group held the first ever learning analytics hackathon at UBC. Participants with a wide range of backgrounds and expertise applied a variety of approaches to analyzing learning-related data. Some used classroom observation data to better understand how learning unfolds, while others used data from a learning management system to identify patterns in how learners use available materials.

According to Leah Macfadyen, program director of Evaluation and Learning Analytics at the Faculty of Arts, the idea for the hackathon came about in one of the group’s weekly meetings, after a member brought in a large data set and asked for help. The group had a lot of fun tossing around ideas about how to analyze the data and how to best present the results. The outcome was so successful that the group wondered, “Why not make it bigger? Why not have a hackathon?”

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