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Tolerance for Ambiguity (TA) is the ability to seek out, enjoy, and excel in ambiguous tasks. This is a skill or mindset that today’s engineering graduates must possess in order to address the problems they must be prepared to solve—problems that are complex, fraught with uncertainty, and given to conflicting interpretations by varying constituents. It can be argued that students with a higher tolerance for ambiguity will be better suited to proactively engage in, enjoy, and excel in finding solutions to the contemporary problems faced by 21st-century engineers. In contrast, students with a lower tolerance for ambiguity may be unmotivated in the modern engineering work environment and struggle to perform well. Given this reality, pedagogical innovations shown to increase students’ tolerance for ambiguity have the potential to better prepare the future engineering workforce. However, there are few examples of how to do this in engineering and/or how to measure the effectiveness of our efforts. This paper briefly describes the development of a pedagogical intervention designed to increase sophomore engineering students’ tolerance for ambiguity. The context of this study is an undergraduate engineering statistics course offered by the Industrial Engineering department at a large university located in the southeast. Students will be given a large hypothetical data set that mimics real data the undergraduate student experience (e.g., GPAs, course completion rates), and asked to use the engineering design process to identify and solve a data-rich problem using statistical techniques they have learned in the course. Two well-established measures of TA were adapted for this study; the result of the face validity check will also be discussed. This paper closes with insights on how these measures will be used to evaluate the impact of the intervention. The findings of this study will not only advance our understanding of pedagogical strategies for fostering the development of this 21st century skill, but also give us meaningful ways to measure the effectiveness of our efforts.