The effects of static and adaptive performance feedback in game-based training

Training in virtual environments (VEs) has the potential to establish mental models and task mastery while providing a safe environment in which to practice. Performance feedback is known to contribute to this learning; however, the most effective ways to provide feedback in VEs have not been established. The present study examined the effects of differing feedback content, focusing on adaptive feedback. Participants learned search procedures during multiple missions in a VE. A control group received only a performance score after each mission. Two groups additionally received either detailed or general feedback after each mission, while two other groups received feedback that adapted based on their performance (either detailed-to-general, or general-to-detailed). Groups that received detailed feedback from the start of training had faster performance improvement than all other groups; however, all feedback groups showed improved performance and by the fourth mission performed at levels above the control group. Results suggest that detailed feedback early in the training cycle is the most beneficial for the fastest learning of new task skills in VEs.

• The type of feedback can impact effective performance and learning of a virtual task.
• Performance feedback was manipulated on type and level of adaptation while learning a task.
• Detailed feedback at initial stages of learning leads to faster increases in performance.
• Receiving detailed feedback at some point leads to better performance, but at different rates.
• Access to training materials does not necessarily lead to self-correction or better performance.