A structural evaluation is imperative for developing an effective virtual learning environment. Understanding the extent to which content that has been learned virtually can be applied practically holds particular importance. A group of persons from the technical field of mechanical and plant engineering (N = 13) participated in a virtual operator training for a case application of additive manufacturing. To evaluate the virtual learning environment the participants answered quantitative questionnaires and were asked to apply what they had learned virtually to the real machine. Both the virtual training and testing phase on the real machine were recorded by video (800 minutes in total). The category system resulting from a structured qualitative video analysis with a total of 568 codes contains design-, instruction- and interaction-related optimisation potentials for further development of the virtual learning sequence. Mistakes, difficulties and other anomalies during the application on the real machine provide further revision options. The study uses video data for the first time to derive optimisation potentials and to investigate the learning transfer of virtually learned action knowledge to the real-world activity.