During the explanatory process, the explainer generally tries to find out whether the person he or she is talking to is following the explanation. To do this, the explainer must perceive non-verbal signals from the other person and adjust their explanation accordingly. Individual and situational factors can influence these social signals. Feedback signals can differ, for example, for people with psychological conditions compared to those without, as well as for people in stressful situations as opposed to those in neutral situations. This diversity of signaling should also be taken into account by Artificial Intelligence (AI) systems when explaining topics to humans.

In the first funding phase, researchers from psychology and computer science investigated the influence of stress and mental health conditions in explanatory situations and were able to show how nonverbal signals that express understanding differ intra- and interindividually. In the second funding phase, the team is developing techniques to train clinical staff to recognize signs of stress in explanatory situations. The findings should help to adapt explanations to the explanatory context and develop more inclusive explanatory techniques.

Research areas: Psychology, Computer science, Linguistics