Let me walk you through this step by step.
First, let's identify the software designer's hypothesis. It's a
causal chain with
three links:
1. Curved key rows → harder to clean between keys
2. Harder to clean → debris (dust, crumbs, etc.) builds up
3. Debris buildup → spring mechanisms deaden → loss of 'play'
To evaluate any hypothesis, we need to test whether the links in its
causal chain actually hold. If any link breaks, the whole hypothesis falls apart.
Now let's check each answer:
A (Same plastics?) - This is about materials, not about cleaning or curvature. Irrelevant to the hypothesis.
B (Does dust impede spring action?) - This directly tests
Link 3. If dust DOES impede springs, the hypothesis gains support. If dust does NOT impede springs, the whole hypothesis collapses — because even if curved keyboards are harder to clean, it wouldn't matter if debris doesn't affect springs.
This is the critical link to test.C (Does deadened play make typing harder?) - This asks about the consequence of the problem, not its cause. We're trying to evaluate WHY play is lost, not what happens after.
D (More complaints about ergonomic keyboards?) - We already know ergonomic keyboards lose play faster.
This just restates the problem rather than testing the explanation.E (Software designers using keyboards more?) - Completely irrelevant to whether curvature causes cleaning difficulty.
The answer is B because it tests the most critical assumption: that debris actually damages spring mechanisms. Without this being true, the entire hypothesis has no foundation.
Answer: BKey Takeaway: For 'evaluate the hypothesis' questions, look for the answer that tests a necessary assumption in the argument's causal chain. The best question to ask is one where a 'yes' answer strengthens and a 'no' answer weakens the argument.