You are a data security engineer. You’ve noticed concerning discrepancies lately that could be a sign of a malicious intruder. How can you convince your department lead to take this threat seriously?
A school counselor contacts you about a troubled student, looking for professional guidance on what to do next. As a developmental psychologist, what advice would you give her?
You are consulting for a town facing groundwater contamination. A local official wants the cheapest remediation plan, but you believe a different approach is more effective in the long term. How could you convince them to adopt your plan?
Real-world assessments offer more than a break from the typical exam format: they enable students to apply recently acquired knowledge to address realistic problems, strengthen understanding and retain what they’ve learned. These forms of assessment can be highly effective in online courses but can also present challenges to create and evaluate, which may deter instructors from implementing these strategies at scale. However, by pairing authentic assessment design with AI-assisted content creation you can create meaningful, applied learning experiences that better reflect the complex work your students will face after graduation.
AI can help you create authentic assessments at scale
AI has potential to reduce your assignment prep time, produce unique learning experiences, and add safeguards against plagiarism. These tools can help you design realistic and variable scenarios and unique-to-each-student data sets while preserving your consistent learning outcomes.
AI can also create grading rubrics to accompany each scenario. The AI-generated, instructor-refined rubric can help you maintain a consistent grading approach across unique assignments.
Let’s look at how AI can support the three example scenarios at the top of this article:
Case study & scenario generation
In the data security example, AI can generate unique threat scenarios for each student. You might prompt AI to create multiple “incident reports,” each describing slightly different system logs, breach points, or suspicious behaviors. Students then play the role of security engineers, writing a brief to a department lead recommending a response strategy. The learning goal of interpreting evidence and communicating technical risk remains constant, but the paths to demonstrate it are unique to each scenario.
Character or symptom variation
In the developmental psychology scenario, AI can create a variety of profiles of child behavior and symptoms. Each student receives a distinct “case file” from a fictional counselor, featuring age, family context, presenting issues, and developmental notes. Students then create their professional response or intervention plan.
Data set creator
For the groundwater contamination example, AI can generate realistic data sets: water quality readings, population health surveys, or cost analyses. Each student or group receives a different community profile, then must interpret the data and recommend a remediation plan.
Ready to try it out? Start small. Choose one existing assignment and use AI to vary the context, dataset, or character details while keeping your learning goals intact. Contact DOE to learn more about how AI can be used to augment your online teaching practice and provide increased opportunity for all your students.