How to Use AI Agents for Formative Assessment in PBL

Using AI Agents to Scale Formative Feedback

Consider a secondary school teacher managing six classes, each working on a different complex, open-ended problem. The challenge is clear: providing timely, formative feedback that respects the learning sciences—specifically the need for immediate knowledge of results—is mathematically impossible to do manually. This teacher needs a way to turn the AI into an effective agent for instruction without losing their pedagogical authority.

Integrating agentic AI into your workflow isn't about replacing your intuition; it is about delegating the heavy lifting of data processing to a tool that understands your specific rubric. By using a problem-based learning (PBL) platform like Saval, you can treat the AI as an assistant that evaluates student reasoning in real-time, allowing you to focus on the "why" behind their mistakes rather than just the "what."

At a Glance

• Best for: School teachers (K-12)
• The problem: Scaling high-quality, real-time formative feedback in open-ended inquiry scenarios.
• Saval capability used: AI-Powered Assessment with teacher-defined rubric strictness.
• Plan needed: Free.
• Time to try it: About 15 minutes to set up a scenario and rubric.

AI agents can perform formative assessment by grading student responses against your teacher-set rubric in seconds. This capability, available on the Free plan, helps you bridge the gap between instructional design and student outcomes.

How to Align AI Adoption with Pedagogical Ethics

The key to successful digital transformation is maintaining the "human-in-the-loop" principle. When you use AI marking, you aren't just letting a black box decide a grade; you are configuring a system that adheres to your pedagogical standards. By adjusting the strictness of the AI, you decide exactly how much grace is given for conceptual errors versus minor syntax issues, ensuring the AI agent acts as an extension of your classroom values.

1. Draft a real-world problem-based scenario that requires students to apply core concepts to a new context.
2. Define your marking criteria clearly—the AI will use this to provide feedback.
3. Configure the AI settings to match your desired level of rigor.
4. Launch the session and have students join via QR code or link.
5. Monitor the Performance Dashboard to see where students are getting stuck in real-time.

What This Means for Your Role

For a classroom teacher, this approach shifts your role from an administrative grader to a facilitator of inquiry. You retain total control over the rubric and the AI's output, which is a vital component of professional AI ethics. The limit remains that the AI cannot replace the nuance of a face-to-face conversation about a student's deeper emotional or social barriers to learning, which is where your expertise remains irreplaceable.

FAQ

How do I ensure the AI grading is fair?

You ensure fairness by setting a clear, objective rubric. On Saval, you define the marking criteria, ensuring the AI evaluates students consistently against those specific learning objectives.

Does this replace project-based learning?

No, Saval focuses on problem-based learning, where students solve distinct, structured challenges. It provides the formative insights you need to guide them through longer-term inquiries.

Takeaways

• Use AI agents to provide instant feedback on formative tasks, allowing you to address misconceptions before they crystallize.
• Maintain control by setting the rubric and adjusting AI strictness to align with your classroom standards.
• Use performance data to pivot your instruction mid-lesson, addressing common student bottlenecks immediately.
• Start small by automating the grading for one specific, recurring challenge type.

Ready to see how this works in your classroom? You can run your first Class Quiz on the Free plan to test how AI feedback helps your students today.