Using AI to Support Competency-Based Assessment Design in Nursing Education

One of the biggest challenges in competency-based assessment is not believing in the concept. Most nurse educators understand the importance of assessing what learners can actually do in practice.

The harder part is the design work.

How do we take a broad competency and translate it into observable behaviors? How do we break down a complex nursing task into the knowledge, skills, attitudes, and clinical reasoning it requires? How do we create assessments that are aligned, meaningful, and realistic for faculty to use?

That is the space where I see AI being useful.

I created Mapping for Competency-Based Assessment as a practical design tool for nurse educators.

The goal is not to replace faculty expertise or professional judgment. The goal is to support the thinking process that sits behind strong assessment design.

Instead of starting with a blank page, educators can use the tool to walk through an authentic practice task, identify what competent performance requires, and begin drafting observable behaviors or assessment ideas.

Used thoughtfully, this type of tool can help faculty:

• translate broad competencies into observable practice

• deconstruct authentic nursing tasks into assessable components

• strengthen alignment across outcomes, learning activities, and assessments

• reduce the cognitive load of assessment design

• support faculty development in competency-based education

Simulation gives us a powerful way to observe complex capabilities like clinical judgment, communication, teamwork, safety, and professionalism. But for simulation to truly support competency-based education, we have to be intentional about what we are assessing, how we are assessing it, and what evidence of performance actually looks like.

A custom GPT will not solve competency-based assessment on its own. Faculty expertise, learner context, program outcomes, and professional judgment still matter most.

But it can serve as a design partner.

It can help educators move from broad competency statements to clearer assessment plans. It can create a starting point for faculty conversation. It can make the early design process feel less overwhelming. And it can help teams build stronger alignment between competencies, learning activities, simulation experiences, and assessment strategies.

The opportunity is not simply using AI in nursing education.

The opportunity is using AI to support better educational design.

For nurse educators doing the hard work of competency-based assessment, that kind of support can be incredibly valuable.