This study showed that students perceived opportunities to revisit assessments (i.e., multistage quizzes/exams) as highly influential on their learning. The explanation for this could be at least two-fold. One possibility is that through this mechanism students had the chance to improve their grade, and it is possible that they could interpret a better grade as a signal that they achieved more learning, which ideally should be true but in reality may or may not be. On the other hand, multistage assessments pose an incentive system in which students not only have to examine their mistakes, but they also have the chance to improve them. It is known that there is a specific type of brain activity linking awareness of error to adaptive learning ). Thus, it is possible that multistage assessments stimulate more of this type of brain activity, and, because of this, students' perception of learning increased. Students also perceived the class environment and instructor feedback to be highly influential on their learning. Barral and colleagues showed that a flipped classroom environment, in which students have more in-class time for activities by moving a large portion of content delivery outside of class, improved student performance in an introductory undergraduate biology course . Additionally, mechanisms to facilitate cooperative learning within the classroom, for example through peer instruction and/or small group or team-based approaches, also improve student performance . Such a flipped model coupled with the incorporation of regular small group work was used in all courses examined in this study, which may thus explain why students perceived the class environment to have a relatively high influence on their learning. It would be remiss not to also mention the importance of instructor attitude and enthusiasm in the class environment, which captures attention thus improving recall and strongly correlates with student intrinsic motivation and vitality . With respect to the influence of instructor feedback on student perceptions of learning, one can appreciate how the brain uses feedback to learn by considering some relevant analogies; artificial neural networks using learning algorithms rely on feedback to recognize patterns , and iterative feedback mechanisms are used in machine and biological learning alike . Regarding its impact on learning, feedback needs to be timely, specific, and actionable to be most effective. The use of feedback to shape learning has been formalized often for example in the training of physicians .