Impact of feedback content in initial learning of an office system

The ability to discriminate between correct and incorrect behavior is essential for learning to take place. This is usually accomplished via feedback from the environment. However, there has been little systematic work on principles of feedback in order to promote optimal acquisition of new skills. The study presented in this paper investigated different types of feedback content in the context of an on-line learning-by-doing tutorial for an office management system. The results suggest that blocking of errors by means of a “scenario machine” is a somewhat beneficial type of feedback, but that including positive content can make learning even more efficient. Feedback about the goals of a tasks or the steps necessary to perform typical tasks were found to promote faster learning and better performance on tasks when informative feedback was withdrawn. Implications for design and analysis of interfaces are discussed.