How do we learn to drive a car? A teacher sits next to us and gives explicit instructions about the components that we need to interact interact with, the rules of the road, and directions to turn. But there are parts of driving that we get used to without such explicit instructions like adjusting to minor curves in the road, adjusting to the steering height and weight, adjusting how hard we push the breaks and the gas pedal to stop. In this thesis, through simpler versions of learning tasks and computational modeling, I investigate how the explicit and implicit learning components interact to allow us to adapt to changing environments. Specifically, this thesis, while focusing on motor learning, investigates the nature of instructions, the magnitude of required adaptation, and the nature of feedback we receive as key factors that control the proportion of how much we rely on our implicit and explicit learning. The first chapter introduces the implicit vs explicit learning literature in context of a simplistic laboratory task called “Visuomotor Adaptation". Chapter 2 discusses a version of the Visuomotor adaptation task study that was conducted and analyzed to assess the importance of task instructions, and adaptation magnitude on implicit and explicit learning. Finally, chapter 3 modifies the visuomotor adaptation task and discusses the effect of the nature of feedback participants received while they were adapting to the experimentally induced motor manipulation.