To develop robots that effectively interact with humans, it is important to understand how humans teach and learn in different scenarios. The research aims to collect data for pairs of humans performing collaborative object-moving tasks in a virtual environment. This is performed for two scenarios, first, when both the agents have complete information about the goal and second, when one only has partial information about it. The data is analyzed for the above-mentioned scenarios. In both scenarios, probability distributions of actions are evaluated for both agents and are compared to understand behavior when goal-teaching is involved and when it isn’t.