Learning Analytics Hackathon 2.0 @UBC

Event Date & Time

  • January 28, 2017 - January 29, 2017
    10:15 am - 7:00 pm

Event Description

***Please note this event is now full. Click “Register Now” to register for the WAITLIST only***

Please join us for the 2nd UBC Learning Analytics Hackathon January 28th-29th.

Our aim is to bring together students, researchers, faculty, staff, and any other interested individuals to get hands-on experience with analyzing learning data. During this two-day hackathon you will form teams, explore our MOOC data from UBCx, propose questions and solutions to those questions, and then show off what you accomplished at the end of the weekend with a brief presentation.

This year we will provide you with UBCx MOOC data to question and explore. Ever wondered how students progress through a MOOC? What patterns emerge about students and learning? What MOOC data looks like? Do you have some ideas for analysis that might give insight into this data? Can you think of a way to appropriately visualize this data? If you have the desire to explore educational data, or to even just learn more about learning analytics, data analysis and/or visualization then we are looking for you to join us!

In addition to registering, please take a minute to complete this quick survey to help us understand who our participants will be: https://goo.gl/forms/ArrPiFK84t22Y22d2.

We will provide data, space, mentoring, refreshments, and lunches. No prior experience is necessary.

Organized by the Institute for Scholarship of Teaching and Learning (http://isotl.ctlt.ubc.ca/) and by Learning Analytics, Visual Analytics (https://blogs.ubc.ca/lava/about-lava/). Want to learn more? Read and watch about last year’s hackathon here.

Please note, this event takes place in Irving K Barber Learning  Centre, Lillooet (301) and Dodson Room (302).

More Event Details

Don’t see what you’re looking for here? Feel free to contact Alison Myers (alison.myers (at) sauder.ubc.ca) or Ido Roll (ido.roll (at) ubc.ca) or ask on our Facebook Event Page!


We said “no experience necessary” and we meant it! We are offering mini-workshops (2 hour sessions on the morning of January 28th) for anyone who feels like they might need a little inspiration/instruction before diving into the data. We have added a question to our Registration Survey for you to indicate your interest in participating in one of the workshops we have provided. If you have already completed the survey, we will be in touch.

Workshop A: Visual Analytics Primer

Presented by: VIVA

Skill Level: Beginner

Have you heard of Visual Analytics (VA)? Not quite sure what it’s all about? Find out how interactive visualization techniques can benefit your data exploration, analysis, and results dissemination through a 2-hour workshop that includes case studies and live demos. Bonus: In this primer, you will get tips on data ingestion and practical strategies for exploratory visual analysis.

P.S. VIVA provides some great resources for Visual Communication, Statistics, Data Wrangling, and Critical Thinking

Workshop B: Data Science in R – Intro to programmatic data analysis

Presented by: Stephen Lee

Skill level: Beginner

R and R Studio are powerful and easy to use tools for statistical computing and data analysis. From importing data to producing informative and aesthetically pleasing plots, the tidyverse package in R incorporates best practices in data science so that you can easily make informative interpretations about your data. This hands-on workshop will accommodate even those who have no experience using R and R Studio and will cover many facets of the tidyverse package including data import using readr, data manipulation with dplyr and data visualization using ggplot.

Software Requirements: R (3.3.2) MUST be the latest version to install the tidyverse package

R Studio (recommended download link: https://www.rstudio.com/products/rstudio/download/preview/)

Workshop C: Event Series Analysis

Presented by: Leah Macfadyen

Skill Level: Beginner/Intermediate

Interest in temporal analytics – analytics that probe temporal aspects of learning so as to gain insights into the processes through which learning occurs – continues to grow. The study of different temporal patterns (e.g., changes in how students access web resources over time, interact with peers) and their relationship to learning outcomes is a central area of interest. However, analysis of temporal (event sequence) data sets can be particularly challenging due to their complex and dynamic character. This workshop will give a first steps introduction to several approaches and tools for conducting temporal analytics, and we will then spend time in a hands-on session starting to apply one or more of these approaches to the hackathon data set.

Preparing for the Hackathon

What do you need to bring?

  • A coffee mug! (and/or water bottle)
  • Laptop and power cables.
  • Software you might want to use.

What should you do beforehand?

The Data

The data will be available to download the morning of the event (we will provide a link) given your acceptance of our data use agreement. Please note, you will only be able to use this data for the duration of the event after which it must be deleted. You are more than welcome to keep any product/outputs from the work you do over the weekend. The data agreement will outline these requirements in more detail.


Day 1: January 28

Time Event
10:15 am Doors open, registration – In Lillooet Room
10:30 am Welcome and introductions. At this time we will also give instructions for accessing the data.
11am Begin – join a workshop or form teams and begin “hacking”
1pm LUNCH (provided)
5pm* Informal Checkin – in Lillooet Room, 5 min per group

*Yes you’re correct, our event does say until 7pm. We have the rooms until 7pm, but will start wrapping up at 5pm (although teams can continue working on their own if they’d like!)

Day 2: January 29

Time Event
10am Doors open (no welcome/introductions – get back to “hacking”)
1pm LUNCH (provided)/Group wrap-up should begin
4pm Event Wrap-up and Prizes!
5pm END