Affective states during problem solving : The role of feedback, individual performance, and motivation.

Abstract

Individuals who perform a task to achieve a goal undergo different affective states, depending on whether they advance towards their goal or not. Those individuals who are able to perform well are confronted with significantly more goal-advancing situations and more positive affective contexts accordingly than individuals who perform poorly. The main contribution of this thesis is a novel experimental task, namely Luckless Mastermind, that allows computer-aided empirical investigation of affective states during problem solving by providing the same goal-advancing situation to any individual, regardless of actual performance. The robustness of resulting game courses is proven via an extensive-search algorithm. The task paradigm enables analysis of different affective states in terms of peripheral physiological response. Skin conductance response is utilized as physiological signal. Based on Luckless Mastermind, an experimental setup has been developed and implemented to investigate three different hypotheses on affective states during problem solving targeted on objective valence, individual evaluation, and ambition.