Figure 2.

Associative learning and hypothesis testing Markov learning models. L = learned state; GE = guessing after an error response state; GC = guessing after a correct response state; PE = perseveration after an error response state; PC = perseveration after a correct response state; γ = probability of answering correctly while in the guessing state; α = the probability of moving to the learned state (i.e., abstraction); σ = the probability of leaving the perseverative state (i.e., set shifting); π = the probability of answering correctly while in a perseverative state. In the hypothesis testing models, examinees can only transition to the guessing and/or learned states after an error. In the associative learning models, examinees can transition to the guessing and/or learned states after an error or after a correct response.