In Statistics education, it is crucial to emphasize the foundational significance of random selection, which underpins statistical methodologies and ensures unbiased representation of populations in samples. However, students often struggle to grasp the concept's complexities, leading to challenges in applying random selection methods effectively. This paper examines the gap between students' theoretical understanding of randomness and their practical application of this concept. Using an Explanatory Sequential Design, this study presents an instructional activity aimed at teaching the concept of randomness in the selection process and proposes modifications to enhance student comprehension. The activity, implemented in undergraduate Statistics and Psychology courses, involved a name selection exercise designed to highlight the inherent biases in human decision-making. Despite students' initial recognition of the lack of randomness, evidence provided through the seemingly innocuous task of selecting names underscores how easily humans struggle with true random selection, indicating a need for deeper understanding. This activity can be used outside stats classrooms by instructors wishing to incorporate statistical reasoning in their lessons. Through qualitative analysis, it was revealed that students overlooked the introduction of statistical bias through specific selection criteria. This finding underscores the difficulties students face in achieving true randomness when applying the concept in practice. The paper encourages the use of a multi-method approach that integrates qualitative insights and quantitative analysis to enhance student comprehension. By adopting this approach, educators can better equip students to recognize and mitigate biases, thereby improving the efficacy of statistical reasoning instruction.