Innovative, inclusive higher education

A research and development initiative focused on using AI to improve teaching and learning. It builds course-aware AI systems that connect generative AI models with actual course materials through retrieval-augmented generation, so students and instructors receive context-specific academic support rather than generic chatbot responses. The lab develops tools for tutoring, question generation, grading assistance, and study support, within a secure UBCO-hosted environment designed to be accessible, pedagogically aligned, and integrated into university courses.

A learning platform whose content can be personalized to a learner’s needs. Learners switch the customization settings to compare and contrast content: syntax such as Java against Python, or discipline such as mathematics against physics.

A visual, web-based degree-planning platform. Students drag and drop courses across planned years and terms, see missing pre- and co-requisites immediately, and receive soft off-term warnings with recency-weighted offering forecasts. Multiple plans can be explored and saved through what-if analysis. Once a term is ready, its courses export to the Term Scheduler, where a visual section picker, seat-alert tracking, auto-optimized timetables, and side-by-side comparison make building a conflict-free week straightforward. The Course Insights pane adds prerequisite graphs, historical offering heatmaps, and multi-year grade-distribution charts, so decisions are informed before registration in Workday.

Future work includes optimization-based recommendation: suggesting courses for the coming term from a student’s progress and degree requirements, and suggesting sections from their schedule preferences and the term’s offerings.

Refer to the official calendar to verify degree requirements and course prerequisites.

TAMS streamlines the TA allocation process at UBCO, guiding each role through its core tasks. Administrators define terms and discipline scopes; coordinators create sessions and manage assignments; instructors submit TA preferences and post-term reviews; students apply for positions, keep their schedules current, and handle post-acceptance changes. The system enforces strong password security, offers secure account recovery, syncs course data from Workday, checks schedule conflicts automatically, and records audit, security, and system events for oversight. Interactive help provides role-specific guidance on workflows, permissions, and post-accept processes.

Future work includes an optimization-based decision support system allocating TAs to courses and labs using linear integer programming under soft and hard constraints.

Still experimental; not an official process.