Research

AI is not a magic fix. Here is the evidence.

Many school leaders are being told AI is the answer. Dr. Karen Abrams tested that promise with students in Guyana in a randomized controlled trial. We share what it found so you can make better decisions for your school.

The question

Does adding AI to a digital learning platform improve how much students learn?

The study took place in STEMGuyana’s Learning Pods, a network of community after-school centers supported by the Inter-American Development Bank’s IDB Lab. The pods serve learners in all ten regions of Guyana, many in communities without internet access at home.

Ten pods were randomly assigned to one of two versions of the same platform. Both groups had the same Ministry-aligned lessons and the same in-person facilitators. The AI version added an AI tutor, AI-generated practice quizzes, mastery-based progression and text-to-speech. The AI features were the only difference between the groups.

What we found

AI features alone did not improve outcomes.

01

No short-term advantage

After eight weeks, learners on the AI-enhanced platform did not show statistically significant gains in Mathematics or English over learners on the non-AI version. The result held after accounting for differences between pods.

02

Minutes are not engagement

Total time logged on the platform did not predict learning gains. Where access is interrupted, logged minutes can reflect connectivity and circumstance as much as real learning.

03

Having a tool is not using it well

How much students used the AI tutor, AI quizzes or text-to-speech did not predict gains. Heavier use may point to a student who needs more help, not one who is getting ahead.

“The future of this work lies not in asking whether AI works in the abstract, but in asking under what conditions, for which learners, and with what forms of support AI can contribute meaningfully to learning.”

Abrams, K. (2026), Chapter 6

For school leaders

Five questions to ask before your school adopts an AI tool.

These come directly from the study’s findings. Ask them of any vendor, including us.

  1. Who will guide students when they use it?

    AI features added without a change in human support did not raise outcomes. The study concludes that AI works best inside clear routines with human facilitation.

  2. Are our teachers prepared to build it into their lessons?

    Access to a tool does not mean it gets used well. Facilitators need training in when and how to use AI so it strengthens learning instead of fragmenting it.

  3. How will we measure learning, not just usage?

    Time on the platform did not predict gains. Dashboards full of logins and minutes can look like success without showing whether students learned.

  4. Does it fit our students’ ages and readiness?

    Students who are still building foundational reading and math skills may need stronger support before AI tools help. What suits a high-school student may not suit a third grader.

  5. What is the evidence, and over what time frame?

    Ask for independent studies with a comparison group, not only testimonials. Short pilots can miss effects in either direction, so plan to evaluate over time.

How the research shapes our work

We educate first, so your community can decide for itself.

Leaders

Understand AI well enough to set policy, evaluate products with clear eyes and build a realistic roadmap.

Teachers

Learn what AI can and cannot do, practice responsible classroom use and earn certification before leading lessons.

Students

Teacher-guided, age-appropriate lessons on how AI works, where it goes wrong and when to question it.

Parents

Plain-language learning on AI at home, online safety and supporting homework, when your school is ready.

Why the evidence is credible

A rigorous design in a setting that is rarely studied.

  • Randomized at the pod level so learners in the same room never saw both versions
  • Same curriculum, lessons and facilitators in both groups, isolating the effect of AI
  • Multilevel statistical models that account for differences between pods
  • Evidence from a Caribbean, low-resource context, which most AI-in-education research does not cover

What the study could not tell us

The intervention ran for eight weeks across a wide grade range, and engagement was measured through platform logs. Longer use, a narrower age group, or measures of confidence and persistence might show effects this study could not detect. We state these limits because schools deserve an honest account of the evidence.

Beyond the study

Experience at national scale.

Through STEM Guyana’s live online AI for Teachers workshops, educators learned how AI works, where it helps and where it falls short, how to use it in lesson planning, and how to handle ethics and age-appropriate use. Certificates were earned by passing an assessment, not by attendance alone.

As Director of STEMGuyana, Dr. Karen Abrams also led the Learning Pods program across all ten regions of Guyana.

671teachers trained
485earned a certificate
40community learning pods in all 10 regions

Cite this work

Abrams, K. (2026). Evaluating the impact of AI-driven tutoring on academic outcomes and engagement in STEMGuyana’s learning pods [Doctoral dissertation, University of Florida].

Dr. Karen Abrams, Ed.D., Educational Technology, University of Florida · Committee chair: Anthony Botelho

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