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What does “detailed feedback” actually look like? This shows you: a real prompt, a real student response, and the structured feedback the platform produces — strengths, weak spots, and a concrete next step.
Step 1 — the prompt
Evaluate the argument
P1. Every swan I have observed has been white.
P2. Therefore, all swans are white.
Is this argument deductively valid? Sound? If neither, characterize what kind of inference it is and what its weakest link is.
Step 2 — a sample student answer
The argument is not deductively valid because the conclusion goes beyond the evidence — the premises don't strictly entail the conclusion. It's an inductive generalization from a sample. The weakest link is the jump from "swans I have seen" to "all swans," since the sample may not be representative: I might live in a region with only white swans.
Step 3 — detailed feedback
Strengths
- Correctly identifies the argument as inductive rather than deductive, and explains why — the premises don't strictly entail the conclusion.
- Names the specific epistemic issue: sample representativeness. This is the heart of inductive risk.
Where to sharpen
- You said the argument is "not valid" — technically deductive validity doesn't apply to inductive arguments at all, so better to say validity is the wrong standard here.
- The sample-size point is good but could name a second issue: even a representative sample doesn't establish universal claims, only probabilistic ones. The form "all S are P" is too strong for any finite evidence.
Next step
- Rewrite P2 as a defensible inductive conclusion. What's the strongest claim the premises actually support?
This is a fixed example so the page loads instantly. On your own responses, a deterministic rubric decides the score; a language model only explains it. Free accounts get 15 detailed-feedback responses a month; Student Pro is unlimited.
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