Flagship initiatives withing the broader Learning Analytics program of activities are as follows: 

Data-Driven Design: Quercus Analytics (D3:QA) 

This initiative provides support to instructors to use student data to make course redesign decisions aimed at improving instruction and learner experience. A cohort of six instructors from various divisions have explored Quercus learner data through analysis of downloaded course activity and quiz reports with support from learning data analysts. Visit the D3:QA Project page for more information.  

Instructor-Facing Quercus Dashboard  

Phase 1 of this project has involved extensive community consultation in planning for a set of user-friendly dashboards, which can be accessed by any instructor to inform course design and pedagogical outcomes.   As a result of the consultations, the first priority identified for exploration and proof of concept was it student activity and progression through course digital resources and the ability to track the type of activity throughout the term (e.g., number of clicks by day and by resource). Phase 2 is focused on development of integrated prototypes, using Quercus data to address this first priority area . Visit Quercus Instructor-Facing Dashboard Project page for more information  

Program-Level Data Exploration 

This project is engaging a departmental team in collaboratively developing a series of questions that explore how course-level data can inform program-level design.   The departmental team is working with a data analyst to identify required data, produce analyses and visualizations of the data, review results, and propose changes to curriculum and program structure.  In the current initial phase, this project will provide a proof of concept for availability of data, data governance and workflows to extract and analyze data using existing and/or manual processes.  It will also inform development of future program level reporting processes and dashboard tools, to improve student learning outcomes within program areas. The main source of data for this pilot is student activity data from the Quercus learning management system. Quercus Record Store 

In order to create infrastructure for the delivery of learning management system data to current and future learning analytics projects, work is underway to architect and implement the Quercus Record Store (QRS), which will allow the University of Toronto (UofT) to leverage Canvas Data Services (CDS) to ingest, store, process and analyze Quercus usage data securely and at scale.  Data from the QRS will be integrated into the institutional data hub to allow for analysis alongside other administrative information sources. A key objective of the QRS is to facilitate data analysis through the creation of curated datasets that will be used for the Instructor-Facing Quercus Dashboards. Tooling will also be implemented to power ad hoc and prepared operational reports run against the full CDS dataset.