Assessing impact of instruction treatments on positive test selection in hypothesis testing

The role of factors previously implicated as leading to confirmation bias during hypothesis testing was explored. Confirmation bias is a phenomenon in which people select cases for testing when the expected results of the case are more likely to support their current belief than falsify it. Klayman (1995) proposed three primary determinants for confirmation bias. Klayman and his colleagues proposed that a general positive testing strategy leads to the phenomenon of confirmation bias. According to Klayman’s account, participants in previous research were not actively working to support their hypothesis. Rather, they were applying a valid hypothesis testing strategy that works well outside of laboratory tasks. In laboratory tasks, such as Wason’s 2-4-6 task (Wason, 1960), the strategy failed because the nature of the task takes advantage of particular flaws in the positive testing behavior participants learned through their experience with the real-world. Given Klayman’s proposed set of determinants for the positive testing strategy phenomenon, treatments were developed that would directly violate the assumptions supporting application of the positive testing strategy. If participants were able to identify and act on these violations of the assumptions, the number of positive tests was expected to be reduced. The test selection portion of the Mynatt, Doherty, and Tweney (1977) microworld experiment was modified with additional instruction conditions and a new scenario description to investigate the impact of the treatments to reduce confirmation bias in test selection. Despite expectations, the thematic content modifications and determinant-targeting instruction conditions had no effect on participant positive test selection