We’re excited to announce the second round of our roundtable conversation series.
After receiving insightful suggestions from our previous series, feedback and points to ponder, we want to continue building this platform for conversation. The last theme centered on artifact scoring, which is one of the most burdensome parts of evidence generation for direct evaluation in accreditation processes.
It is also the most crucial component when considering AI-related solutions. The stakes are high, and accuracy drives everything that follows. Curricular recommendations, rescoring, and closing the loop all require accurate calibration of the rubric to begin with.
From what we heard, even selecting an artifact for a given program learning outcome can be challenging when rubric definitions are too vague or subjective to reliably identify the right artifact. This can lead to an even bigger problem: scoring the wrong artifacts.
We want to help reduce the time and burden on faculty. The solution we’ve narrowed in on is a comprehensive rubric design that consistently supports:
Consistent artifact scoring by faculty or AI
Rubric definitions that lead to better artifact selection
Starting next month, we’ll be running the same structure: exploring the use case of rubric design in accreditation, hosting a practical workshop on designing an agent to build rubrics, and discussing governance concerns when applying agentic AI to rubric design.
Module 1: The applied use case of rubric design in accreditation, and how agentic AI can help
Module 2: Workshop, designing an agent to build rubrics
Module 3 : Governance and guardrails for agentic AI in rubric design
Registration will be opening soon. Please stay tuned for the details! As before, we’re keeping the group small to keep it a conversation rather than a webinar.
If you were in the room for round one, thank you. This next series exists because of what you raised. If this is your first time joining, welcome in.