Talks

Course Insights: Unified Learning Analytics Platform for Instructors

Presenters: Jeff Longland, Justin Lee

June 18, 2025

The LT Hub Learning Analytics team at UBC is developing Course Insights, an instructor-facing platform designed to centralize data from systems like Canvas and the Student Information System (SIS) into a single, user-friendly web application. Initially developed in response to urgent instructor needs during the COVID-19 shift to online teaching, the platform provides accessible, self-serve data on student engagement, performance, and course activity.

A key feature, Equity Insights, was developed in collaboration with the Faculty of Science to support inclusive teaching by enabling instructors—after an orientation—to explore grade distributions by demographic groups. Inspired by pedagogical research and direct instructor feedback, Course Insights continues to evolve with planned features such as Know Your Students, which will provide insight into students’ academic backgrounds.

Ongoing development is guided by the Learning Analytics Faculty Partnership Program, which fosters inquiry-driven enhancements to the platform. Ultimately, Course Insights aims to empower evidence-informed, equitable, and responsive teaching practices.

Calling all Canvas data wranglers​: Collecting wisdom and catalyzing action from the SoLAR community​

Presenters: Craig Thompson, Alison Myers

June 18, 2025

Several SoLAR institutional members use Instructure’s Canvas as their Learning Management System. Instructure provides several means of extracting data from the LMS such as: Canvas API, Canvas Data 2, Canvas Live Events / Caliper, and reports / dashboards available within the application web interface.

The data accessed via different means is sometimes inconsistent: not all data is available from all sources, data representations differ across sources, and some data is not easily extracted at all.

This lightning talk will serve as a launching point for a few follow-up conversations with individuals who are either responsible for extracting information from Canvas or work closely with information that others have extracted. At present, three follow-up topics of conversation are planned: (1) sharing what data access avenues we use and why, (2) sharing scripts, queries, and data extraction tools, and (3) coordinating a communal effort to seek better data access from Instructure.

UBC Learning Analytics Hackathons for Awareness and Community Engagement

Presenters: Craig Thompson, Justin Lee, Alison Myers

Co-Author: Will Engle

March 20, 2024

Challenges of institutional adoption of learning analytics include lack of student engagement, little transparency, and few opportunities for feedback. In this report, we reflect on one element of our institution’s approach to these challenges: regular engagement of students, practitioners, and institutional leadership through Learning Analytics Hackathons. The history and evolution of these hackathons mirror the advancement of learning analytics at the University of British Columbia: they started as community-driven events but have gained institutional support and attention as our data infrastructure and learning analytics culture matures. At the time of writing, the authors are planning the 9th Learning Analytics Hackathon. In this report, we share our approach, lessons learned, and discuss opportunities for continued student engagement in learning analytics at our institution.

Learning Events and Learning Record Stores: A Practical Introduction

Jeff Longland

April 6, 2023

Much has been written about how data and analytics can unearth new questions and innovative solutions. Data-driven decision models are heralded as part of digital transformation initiatives. Clickstream data can be mined for valuable insights! But what does it *actually* mean for teaching and learning?

This session won’t discuss the hype surrounding data and analytics initiatives. It won’t be academic or research-driven. What it will provide is a practical introduction to learning event standards (eg. xAPI, Caliper), learning record stores, and the work underway at UBC to build data infrastructure for learning data. We’ll cover:

• Who needs learning events? Who is a learning event about?
• What is a learning event?
• When does a learning event occur?
• Where do learning events occur and where do they go?
• Why?

It’s a whirlwind journey through the challenges and opportunities where the learning analytics rubber meets the road. We’ll cover how a learning tool is instrumented to emit events and its journey to a storage location where it can be used to support evidence-informed teaching and learning.

Student Flows – Video

Craig Thompson & Annay Slabikowska

November 5, 2021

A group of analysts at UBC have been collaborating to answer common questions about student progression through courses and programs. In this session we will share lessons learned from our work, as well as tips for success for those interested in undertaking similar initiatives.

Instrumenting for Learning Events at UBC

Jeff Longland

November 5, 2021

An introduction to learning events, learning record stores and the work underway at UBC to build a data system for learning events. We’ll look at how we’ve instrumented learning tools to emit structured events, how events are ingested and stored, then explore examples of how events can be used in instructor and student dashboards.

In-house Video Analytics: Taking advantage of available log data to create contextually-relevant learning analytics dashboards

Alison Myers, Marko Prodanovic, and Sunah Cho

November 5, 2021

Learning Analytics can provide valuable insights to instructors regarding their teaching, however, analytics from vendor tools are often isolated datasets, which do not give the entire picture. We explored how to combine log data about video viewing activity with LMS data about course structure in order to provide our instructors with analytics that included not only student video watching behaviours (from the log data), but also contextual information about their course (from the LMS data). As the field of learning analytics has matured, we often see “scaled” solutions that aim to provide data or insights to an entire institution. However, the goal of “scale” can overshadow the design decisions made by individual instructors, creating analytics that are not relevant or detailed enough for decision making. Our collaboration between the analytics team and a learning designer allowed the focused development of a learning analytics dashboard that is contextually relevant and meaningful for our instructors so that they can use the information to make design decisions to improve their teaching and the student experience.

Putting Data to Work at the University of Michigan – Video

Timothy McKay, University of Michigan

June 20, 2019

On June 20, Timothy A. McKay visited UBC to share his experiences using learning analytics to explore equity and improve learning at the University of Michigan. More than 60 graduate students, faculty, and staff attended McKay’s keynote, which kicked off UBC’s Afternoon of Learning Analytics event.

Learning Analytics at UBC: Establishment of Institutional End-to-End Learning Analytics Capability

Jeff Longland and Craig Thompson

May 2, 2019

Learning analytics (LA) is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. UBC is in the middle of a learning analytics innovation project to build an institutional culture, support capacity, policy framework and technical infrastructure to use LA to drive continuous improvement in the learning environment.