Introduction

Before we explore neuroscience-informed AI and cognitive diversity, let's begin with a simple question.

AI often appears successful because students finish work faster, complete more assignments, or produce higher-quality work. But does that always mean learning has occurred?

Throughout this OER, we will explore how AI can support different kinds of learners. We will also consider how AI can unintentionally hide learning needs or create dependence when it replaces thinking instead of supporting it.

Purpose of This Activity

This opening activity is designed to challenge your first impressions. As you read Maya's story, look beyond grades and completed assignments. Consider what evidence would convince you that AI is helping Maya build understanding, confidence, and independence, rather than simply helping her finish the work.

Before You Continue...

Your answers may have been very different from someone else's. That is because AI can support learning and create new challenges at the same time, depending on the learner and how the technology is used.

Recent research on AI in education suggests that AI can both improve learning and create unintended cognitive risks. As Jose et al. (2025) conclude:

"These findings suggest AI enhances accessibility but may weaken retention if overused. To maximize benefits, AI should support rather than replace human-driven learning strategies." (Jose et al., 2025).

In other words, AI can improve access, reveal learner strengths, reduce barriers, and build confidence. At the same time, it can unintentionally hide learning gaps or create dependence if it begins doing too much of the thinking for the learner.

As you continue through this OER, keep asking yourself:

Is this AI helping the learner think—or thinking for the learner?

In the next activity, you'll meet three learners with different cognitive profiles and consider how AI might support each of them differently.