There is significant interest in research regarding student understanding and performance, especially in probability and statistics. Past research has focused on misconceptions in statistical inference, but, there is little research regarding statistical misconceptions for undergraduate engineering students. Additionally, engineering educators recognize that active-learning strategies can improve undergraduate STEM education, but unfortunately intervention-based research on reducing statistical misconceptions is not prevalent. This research aims to address these literature gaps by employing a simulation-based structured group work activity whose goal was to increase awareness of and help students overcome misconceptions regarding the Central Limit Theorem (CLT). The CLT was chosen based on its abstract, non-intuitive nature, prevalence in the literature, and its foundational importance to the field of probability and statistics. Informed by the work of Schwartz and Bransford, this study draws on contrasting cases in conjunction with a simulation-based group assignment given to undergraduate industrial engineering students enrolled in an intermediate-level probability and statistics course at the University of Pittsburgh. Through this active-learning intervention, the following research questions are addressed: (1) How can active-learning strategies help students overcome misconceptions in statistics? (2) How do active-learning strategies affect the retention of statistical concepts across a curriculum?