People seem to learn tasks even without formal training. This can be modelled as the outcome of a feedback system that accumulates experience. In this paper we investigate such a feedback system, following an iterative research approach. A feedback loop is specified that is detailed using contemporary ideas on human behaviour. The resulting model is investigated in an empirical study. Finally, we consider a computational mechanism to explain the results. This approach is aimed at understanding how a feedback mechanism might work rather than at observing its outcomes. In this paper, we study the approach through adjustments in card selections in a game consisting of repeated card choices. Playing this game, participants do not know what rules determine gains and losses. Therefore there is some tension between exploring the options and achieving immediate profit. To decide in such situations it is argued that often evaluations below the level of conscious awareness, such as affect, play an important role. The results support the hypothesis that participants would draw better cards as the game progressed. There is some evidence that emotions are involved, since the hypothesis that profit and emotions are correlated is confirmed. Further evidence that formal logic is not sufficient follows from the observed effects of music on card selections. In the second part of the paper the aim is to understand the results from a computational point of view. Four possible ways of integrating feedback into a decision criterion are compared. Using one of these mechanisms, a computational model is investigated that might describe the role of music in card selection. Although there are limitations to both the empirical and computational findings, the chosen approach indicates that computational modelling of experiential appraisal, at a preconscious level, and the effect of external factors, such as music, is in principle feasible, and can lead to a research agenda aimed at understanding such phenomena.