Active or engaged learning is often seen as a way to improve students’ performance concerning STEM topics. When following such a form of self-directed learning, students often need to receive feedback on their progress. Giving real-time feedback on an individual basis is usually beyond the teacher’s capacity; in digital learning environments, this opens the door for exploring automated feedback. In the current study, a posttest only design was used to investigate the effect of providing students with different forms of automated feedback while they were creating a concept map about photosynthesis in an online inquiry learning environment. Participants were high school students (N = 138), divided over two experimental groups. In one group, feedback was given by a humanoid robot and in the other group via an avatar. The effects of the different feedback forms were compared for the two groups in terms of the frequency with which students consulted the feedback, concept map quality, and students’ attitudes. Results showed that the robot group consulted feedback more often than the avatar group. Moreover, the robot group had higher scores on a scale measuring enjoyment than the avatar group. Both of these differences were statistically significant. However, the average quality of the concept maps created by both groups was similar.