| Popis: |
Are students able to learn from exam experience about their level of knowledge for tested topics? Prior to an exam, undergraduates made predictive category learning judgments (CLJs) by estimating the percentage of questions they expected to answer correctly for six topics. After the exam, they made postdictive CLJs for the same topics. Supporting the postdiction superiority hypothesis, postdictive CLJs were slightly more accurate than predictive CLJs, indicating students could make better formative evaluations after taking an exam. However, postdiction accuracy was low, and in a second study, accuracy did not differ for predictive and postdictive CLJs. We also investigated two processes required to make accurate postdictive CLJs: monitoring performance for individual questions and accurately classifying each question with respect to the topic that it assessed. Although students performed these tasks adequately, their less-than-perfect performance would constrain their ability to accurately judge their topical knowledge from exam experience. |
Full Text from ScienceDirect