As emerging technologies like generative AI, large language models (LLMs), and natural language processing (NLP) continue to advance, opportunities to meet the needs of the community through technology become increasingly possible. At UBC’s Cloud Innovation Centre (CIC), leveraging technologies to address relevant community issues lies at the heart of our purpose. In the pursuit of innovation through our many projects, there are times when our projects intersect with the needs of the larger community. These projects provide solutions that have implications for various sectors. Within the education sector, CIC’s Course Flexibility Project was a finalist for the CUCCIO 2024 awards in the Innovation category, recognized for its cutting-edge application of generative AI to address a complex problem in higher education. 

Leveraging generative AI to advance processes

Developed in collaboration with the Office of the Provost & Vice-President Academic (VPAO) and powered by Amazon Web Services, the UBC CIC’s Course Flexibility Project started in 2023 with the goal of creating a streamlined solution that allows users to analyze the pedagogical flexibility of courses from their syllabi.

A large university such as UBC will typically offer thousands of different courses over an academic session. Though it is typical for academic governance processes to provide general guidelines for what should be contained within course syllabi, the specific pedagogical approach is left to the instructor to decide based on the learning goals of the course and the habits and norms of their faculty. Naturally, there is a great degree of variance in how courses are structured, delivered and assessed. This can result in an anecdotal sense of variation in flexibility across courses offered at the institution. Whilst details of a particular course can be understood by simply reading a single syllabus, obtaining an aggregate-level insight into the offerings of instructors at an institutional level is a process that would require the parsing of thousands of pages of text. This hinders the ability to quantify the instructional variations across the full range of an institution’s courses, particularly in the 100-level where much of the course development occurs. 

With course offerings being core to an institution’s value, the ability to easily assess them across specified dimensions is an integral improvement that can benefit faculty, staff and students.  The CIC’s scalable, open-source solution is designed to automate the analysis of syllabi content using AI, NLP, and LLMs to store, extract, and analyze text from syllabus files en-masse. Courses can be filtered by campus or faculty, for field of study or academic level, and across different dimensions of flexibility, such as make-up exam policy, lecture recordings, and other flexibility options. This enables the VPAO to capture a quantitative, aggregated view of flexibility across UBC’s courses. While the prototype focuses specifically on analyzing dimensions of course flexibility, the open-source nature of the application allows for ease of modification and deployment. By changing the guidelines used for semantic comparison, the application can analyze other aspects of syllabi such as “inclusive learning” and “use of generative AI”. Furthermore, other source documentation aside from syllabi could be used to support a generalized approach towards extracting meaningful insights on a given topic from large volumes of textual data, permitting far greater functionality than simple text matching searches. 

The success of the Course Flexibility project serves as a proof-of-concept on how emerging technologies like generative AI can be applied to advance the best practices of higher education. Not only can such solutions streamline existing processes, but they can also add to an institution’s capability by turning tasks that were previously unfeasible into unprecedented possibilities. In this instance, the Course Flexibility project improves the institution’s ability to capture metrics on offered courses, driving pedagogical innovation by supporting the identification of best practices and pain points.  This previously uncaptured information can be leveraged to achieve more consistent student experiences, empowering learners through increased flexibility. 

If you would like to learn more about the CIC’s projects, visit the projects page.