Evaluating AI Learning Tools Before You Buy
Judge AI edtech on evidence, safety, data, accessibility and real classroom fit before you commit
A taste of a lesson
A vendor claims their AI tutor raised test scores by a big margin. What should I ask them?
Ask for the study itself, then check four things. Who ran and funded it? Was there a comparison group that didn't use the tool, and how were groups chosen? Which outcome was measured, a standardised test or the product's own quizzes? And how many learners, over how long, in settings like yours? A gain on the tool's own quizzes after a few weeks means much less than a gain on an independent test. Which of those four do you think their claim will struggle with?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Apply a structured evaluation across evidence, safety, data, accessibility and cost
- Write vendor questions that reveal how a tool handles data and errors
- Read impact claims critically and distinguish evidence types
- Design a small pilot with success and stop criteria set in advance
Lesson plan
- 1 Start with the problem Define the learning or workload problem and current practice before looking at products. Start
- 2 Reading evidence and claims Assess impact claims by method, independence and outcomes measured. Start
- 3 Accuracy, safety and pedagogy testing Test a tool with your own content and edge cases for errors, bias and learning design. Start
- 4 Data, accessibility and contracts Ask the questions your data protection, accessibility and procurement leads will need answered. Start
- 5 Designing the pilot Plan a time limited pilot with success criteria, comparison and stop rules. Start
- 6 Making and documenting the decision Combine findings into a clear recommendation that others can scrutinise. Start
Try asking
About this tutor
For school and university leaders, learning technologists, L&D managers and procurement teams facing a flood of AI learning products. You learn a structured way to evaluate a tool: what learning problem it solves, what evidence exists, how it handles data and age limits, accessibility, bias and accuracy testing, teacher workload, integration, total cost and exit. We practise writing vendor questions, designing a small pilot with clear success criteria, and reading marketing claims critically. This is education, not legal or procurement advice: final decisions follow your organisation's procurement rules and data protection advice.
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About the teacher
Lecturer and learning designer for universities, workplace training and coaching practices
9 tutors 410 lessons taught Sample
My background is university teaching followed by learning design work, building courses with subject experts and turning them into something people can actually learn from. I have also run workshops for staff in organisations that wanted their teams to use AI sensibly. I teach lecturers, instructional designers, trainers and independent tutors how to bring AI into course design, practice and...
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