There is a heated debate right now around AI and assessment.
This is understandable given that AI’s language and reasoning capabilities complicate our ability to genuinely assess student understanding.
Students can generate polished responses in seconds and submit them as their own, which weakens the core purpose of assessment: understanding what students actually know and can do.
Still, I keep coming back to the same point I have argued elsewhere.
The core issue is not AI but assessment design.
When assessment relies too heavily on product over process, AI simply exposes an existing weakness.
My own position is fairly straightforward. I would recommend a hybrid approach to classroom assessment. One strand accommodates AI and leverages its potential to enhance assessment practices.
Another strand remains intentionally AI-free, where students work independently to demonstrate their learning.
The former aligns well with formative assessment, while the latter fits more naturally with summative assessment.
I strongly argue that the real potential of AI lies in formative assessment, that is, assessment for learning.
By definition, formative assessment is “any task that provides feedback to students on their learning achievements during the learning process. It includes, for example, open-ended response questions, essays, and performance tasks, such as posters, presentations or projects.” (Glazer, 2014, p. 277)
In this space, AI can support feedback, revision, reflection, and dialogue without replacing student thinking.
Torrance and Pryor (2001) take this discussion further by distinguishing within formative assessment between convergent and divergent approaches.
Convergent assessment focuses on checking if students can reach a predetermined outcome. Divergent assessment focuses on understanding how students think, what they understand, and how learning can move forward.
I created the visual below based on insights from Torrance and Pryor’s paper to clarify the difference between convergent and divergent assessment.
I highly recommend reading their work. It is old, but it still speaks directly to today’s debates around AI and assessment.
And if you are wondering about the sketch in the visual, I created it using Nano Banana Pro and then refined it in Canva.
References
Glazer, N. (2014). Formative plus Summative Assessment in Large Undergraduate Courses: Why Both? International Journal of Teaching and Learning in Higher Education, 26(2), 276-286.
Torrance, H., & Pryor, J. (2001). Developing formative assessment in the classroom: Using action research to explore and modify theory. British Educational Research Journal, 27(5), 615–631.
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