Discrimination/Slope Item Response Theory Models In item response theory (IRT), 1-PL models, which include a slope parameter in addition to the intercept parameter, are better able to discriminate test-taker talent. Higher slopes translate to steeper sigmoid curves.
But what does a highly discriminative test mean? Why would a steeper slope yield increased learnings about test-takers?

A steeper slope means a stronger relationship between ability and the question. It means that the item (and therefore the test) is more reliable - and reliability is the inverse of measurement error. Less error = better discrimination.
You can get higher reliability / discrimination / less measurement error by having more questions or having questions with larger slope parameters.
