Since targeted students already consume AI every day through search engines, recommendations, and chatbots, I initiated the development by framing AI as something they actively use, not just something to learn about.

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I began by simplifying complex ideas like ethical AI and bias using relatable analogies. By comparing AI to everyday consumption, students could see how what they input and what systems are trained on shape what they receive.

To keep the experience cognitively accessible, I structured the module into short, focused segments. This shifted the experience from abstract understanding to real decision-making.

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Using Articulate Storyline, I designed interactive elements, such as click-to-reveal, dragging the slider, and branching scenarios with immediate feedback. These interactions were intentionally designed to encourage reflection and reasoning, rather than quick right-or-wrong answers.

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Assessment remained formative, using decision-based prompts and reflection to build early awareness and critical thinking habits. For this, I also brought in real chatbot responses, asking students to analyse and compare outputs to identify what makes a response fair, biased, or incomplete.

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The result is an experience that helps students question the AI they consume daily, recognise bias in real outputs, and make more informed decisions as users.

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Click below to explore this micro-learning.