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This research-to-practice full paper presents and approach to bringing convergence to the undergraduate engineering context. Convergence is the process of integrating a variety of ideas, skills, and methods to create new ideas, skills, and methods in order to address complex, socially relevant challenges like the UN Sustainable Development Goals [1] and the National Academy of Engineering's (NAE) Grand Challenges [2]. In the US, the National Science Foundation (NSF) has been a major driver of convergence related research and has focused on work primarily at the graduate level and beyond. To explore how convergence concepts translate to an undergraduate engineering context this research to practice paper describes a taxonomy that translates convergent knowledge, skills, and mindsets into the domain of undergraduate engineering education. While we do not believe it is reasonable to expect undergraduates to engage with convergence in the same way as graduate students or postdoctoral scholars, we believe that they can develop in areas that will allow them to engage in convergent work later in their careers. This paper first defines convergence and then examines the challenges and opportunities related to developing a student's ability to do convergent work in an undergraduate context. The developed taxonomy outlines the knowledge, skills, mindsets, and structures that support convergent work from the larger research literature, and adapts these to an undergraduate context. The taxonomy is then used to conduct a gap analysis of an undergraduate electrical and computer engineering degree program. This analysis is based on the syllabi. This work was conducted in the context of an electrical and computer engineering department situated in a medium-sized primarily undergraduate liberal arts institution in the mid-Atlantic region. As the challenges and opportunities are similar to but also unique to this institution this work forms a rich case study that can inform similar efforts in other institutions and contexts where a similar gap analysis may be beneficial. The goal of this work is to enable others to analyze an their existing student experience to see what aspects of convergence are currently included. 

Abstract—Wicked problems, the National Academy of Engineering’s Grand Challenges, the United Nations’ Sustainability Goals, and similar complex, global-scale endeavors fall under the broad umbrella of “convergent” work. Over the past two decades there has been an increase in interest and funding for work in this space. The NSF has two programs focused in this area, Growing Convergence Research and the Convergence Accelerator. Boston University’s College of Engineering recently announced a focus on convergent projects and work. The National Academic of Engineering also has the Grand Challenge Scholars program with over 100 participating schools. The list continues to grow. The broad concept of convergence seems to be quite simple: combine the ideas, skills, and/or methods of multiple disciplines to create something new. More specific definitions vary and while the interest in convergence and convergent problems continues to increase, there is no easily operational definition of convergence. This is especially true with respect to undergraduate-level education where students have limited experience and knowledge to carry out such efforts. To better understand the variation that exists within the literature on convergence we conducted a systematic review to explore how convergence is defined in scholarly literature. We have identified a small number of categories within the definition space and conducted a thematic analysis of the aspects of each. The results show that there is a fairly consistent focus on the work being socially-relevant and on creating something new such as an idea, method, product, or process to address desired needs. Additionally, doing convergent work requires the integration of aspects of multiple disciplines and is conducted by diverse teams. Lastly, the disciplinary backgrounds of those teams almost always includes the natural and biological sciences with a subset the following disciplines: information or computing sciences, engineering, social sciences, and humanities. While there is some consistency in the definition, there also seems to be space for some variation which leaves for some level of choice in the definition.