Social learning processes in quantitative estimation tasks

The present thesis investigates social learning processes in quantitative estimation tasks with a focus on two different social contexts. The first part concentrates on interacting groups and examines G-I transfer, which denotes an increase in individual performance due to group interaction, for example, through acquiring certain skills or knowledge from the other group members. Whereas such G-I transfer has been successfully shown for problem-solving tasks, evidence for G-I transfer on quantitative estimation tasks is scarce. The present thesis addresses this research gap with a focus on how often a group has to interact in order to fully exploit the benefit of this learning effect. Results from two experiments support the idea that a single group interaction is sufficient to induce a stable G-I transfer. In contrast to nominal groups, both members of continuously interacting groups and members of groups with only one initial interaction exhibited stable G-I transfer, and the size of this transfer did not significantly differ between the latter two conditions. Based on the assumed simplicity of this learning process, the second part of the present thesis examines a social context without direct interaction, namely advice situations in the judge-advisor paradigm. Previous research in this paradigm has focused on how judges weight advice, and on the beneficial effect of receiving advice on judges’ post-advice final judgments. However, social learning processes could improve the accuracy of judges’ subsequent initial judgments as well. Hence, it is assumed that advice can induce individual performance enhancements that differ as a function of the advisor’s judgment accuracy. The results of three experiments support this hypothesis and indicate positive social learning particularly when participants receive high quality advice even without feedback about its quality. In general, the results suggest that interacting with others as well as receiving advice can have a positive effect on subsequent quantitative estimation in terms of social learning and hint at the importance of reference values for these learning processes