Discussion:
Assessment has traditionally been a static and time-consuming aspect of education, limited to exams, quizzes, and manual grading. With generative AI, it is now possible to create personalized, adaptive assessments on the fly. These assessments can respond to individual learner progress, provide instant feedback, and even suggest next steps for growth. AI can also analyze patterns across cohorts to identify common misconceptions or areas requiring targeted intervention. The potential extends beyond formal testing: formative, creative, and competency-based evaluations can be automated while remaining meaningful and actionable.
Inspiration:
AI-Crafted Assessments represent a frontier where mobility and intelligence converge to make assessment as dynamic and personalized as learning itself. For educators, this offers opportunities to focus on coaching, mentoring, and designing rich learning experiences rather than administrative grading. For learners, it means immediate, tailored feedback that guides growth and keeps motivation high. This frontier is transformative because it shifts assessment from a static snapshot to a continuous, personalized dialogue — a change that could redefine teaching and learning in the coming decade.
In my current L&D role, one of the biggest challenges is creating fair, scalable, and meaningful assessments for staff training. Currently, training evaluations are completed manually and limited to completion rates or post-training surveys. AI-crafted assessments could change this by personalizing evaluations to the learner’s level and giving real-time feedback. For me, I wonder how it could move beyond basic reporting into evidence-based learning analytics.
I’m really keen on exploring this space, as I truly think there’s a ton of potential growth opportunities for educators to explore. The ideas presented above all offer interesting opportunities within our formal education spaces (and beyond), and I’d offer one further example that I think I had overlooked until just recently. AI-assisted assessment has tremendous potential to not only increase the personalized and authentic assessment spaces, but could also help in professional development settings where there are requirements to maintain a certain level of competency in order to be deemed an active (and up-to-date) member of a professional association.
Gen-AI could be repurposed to serve up summative and/or formative assessments for this group of professionals and offer them a chance to continue to grow beyond their formal education, as well as, help the requisite association report on its membership’s ongoing continuous PD. This mechanism could form the basis for governing bodies to maintain and protect their members, and also bring membership up-to-speed where large-scale paradigm shifts happen.
I think as AI continues to improve, it will continue to gain importance in my career as a teacher. I have already seen a difference in my teaching and how I allocate my time in assessing my students learning progress. Rather than spending hours on rubrics for manual grading, I can set AI to create adjustive, personalized assessments for every student. They would receive feedback tailored to each child’s progress, deepening my understanding of their needs to better assist them. Moreover, I can invest more time on my students, shifting from routine to more purposeful engaging learning activities. My fourth graders would appreciate more how learning assessments are aimed at their diverse needs, stimulating their confidence and growth. The transformation from static to ongoing dynamic assessment is a valuable technological advancement in primary level schooling.
AI-crafted assessments are one of the most compelling frontiers because they can fundamentally shift the way educators teach and how students learn. Instead of being content-heavy and focused on memorization or multiple-choice testing, assessments can become more skills-based and reflective, asking students to apply what they’ve learned to real-life contexts. This approach challenges educators to rethink their role, moving away from grading and toward mentoring, guiding, and supporting deeper learning.
I am always supportive of any technology that can give educators back there time. Direct time with students are were our educators are best used, and are best appreciated by students. AI has potential to redefine assessment time-management for educators, albeit immaturely at the moment.
I don’t trust AI, yet, to fully assess for me. Although it is a fantastic foundation.
I think AI-crafted assessments could reshape school learning in important ways. Traditional quizzes and tests often give students a single score with little explanation, but AI powered mobile devices have the potential to provide immediate feedback that actually helps students understand mistakes. Instead of waiting for a teacher to return a test, students could get guidance in the moment and adjust their learning as they go.
It is easy to imagine math students receive hints that guide them through a problem step by step, helping them not only spot errors but also see the reasoning process they may have missed. Similarly, language learners could get corrections as they write (or even as they speak), with the AI offering suggestions on grammar, vocabulary, pronunciation and style in real time. This is definitely an interesting frontier with a broad horizon.