We explored the complex interplay between students' affective states and problem solving outcomes. We conducted a study where 41 students solved 28 analytical reasoning problems from the Law School Admission Test. Participants viewed videos of their interaction history and judged their emotions at theoretically relevant points in the problem solving session (after new problem is displayed, in the midst of problem solving, after feedback is received). We explore excitatory and inhibitory relationships between the affective states and problem solving outcomes (i.e. success or failure, and associated positive or negative feedback). We isolate affective states that are consequences of outcomes and associated feedback as well as affective states that are antecedents of positive or negative outcomes. Follow-up analyses focused on cyclical patterns that incorporate complex relationships between the affective states and problem solving outcomes. Implications of our results for affect-sensitive artificial learning environments are discussed.