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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. 

Education literature has long emphasized the compounding benefits of reflective practice. Although reflection has largely been used as a tool for developing writing skills, contemporary research has explored its contributions to other disciplines including professional occupations such as nursing, teaching and engineering. Reflective assignments encourage engineering students to think critically about the impact engineers can and should have in the global community and their future role in engineering. The Department of Electrical and Computer Engineering at a small liberal arts college adopted ePortfolios in a first-year design course to encourage students to reframe their experiences and cultivate their identities as engineers. Our recent work demonstrated that students who create ePortfolios cultivate habits of reflective thinking that continue in subsequent courses within our program’s design sequence. However, student ability to transfer reflective habits across domains has remained unclear and encouraging critical engagement beyond the focused scope of technical content within more traditional core engineering courses is often difficult. In this work, we analyze students’ ability to transfer habits of reflective thinking across domains from courses within a designfocused course sequence to technical content-focused courses within a degree program. Extending reflection into core courses in a curriculum is important for several reasons. First, it stimulates metacognition which enables students to transfer content to future courses. Second, it builds students’ ability to think critically about technical subject matter. And third, it contributes to the ongoing development of their identities as engineers. Particularly for students traditionally underrepresented in engineering, the ability to integrate prior experiences and interests into one’s evolving engineering identity may lead to better retention and sense of belonging in the profession. In the first-year design course, electrical and computer engineering students (N=28) at a liberal arts university completed an ePortfolio assignment to explore the discipline. Using a combination of inductive and deductive coding techniques, multiple members of our team coded student reports and checked for intercoder reliability. Previously, we found that students’ reflection dramatically improved in the second-year design course [1]. Drawing upon Hatton and Smith’s (1995) categorizations of reflective thinking [2], we observed that students were particularly proficient in Dialogic Reflection, or reflection that relates to their own histories, interests, and experiences. In this paper, we compare the quality of student reflections in the second-year design course with those in a second-year required technical course to discover if reflective capabilities have transferred into a technical domain. We discovered that students are able to transfer reflective thinking across different types of courses, including those emphasizing technical content, after a single ePortfolio activity. Furthermore, we identified a similar pattern of improvement most notably in Dialogic Reflection. This finding indicates that students are developing sustained habits of reflective thinking. As a result, we anticipate an increase in their ability to retain core engineering concepts throughout the curriculum. Our future plans are to expand ePortfolio usage to all design courses as well as some 

Medical Cyber-physical Systems (MCPS) are vulnerable to accidental or malicious faults that can target their controllers and cause safety hazards and harm to patients. This paper proposes a combined model and data-driven approach for designing context-aware monitors that can detect early signs of hazards and mitigate them in MCPS. We present a framework for formal specification of unsafe system context using Signal Temporal Logic (STL) combined with an optimization method for patient-specific refinement of STL formulas based on real or simulated faulty data from the closed-loop system for the generation of monitor logic. We evaluate our approach in simulation using two state-of-the-art closed-loop Artificial Pancreas Systems (APS). The results show the context-aware monitor achieves up to 1.4 times increase in average hazard prediction accuracy (F1score) over several baseline monitors, reduces false-positive and false-negative rates, and enables hazard mitigation with a 54% success rate while decreasing the average risk for patients. 

Medical Cyber-physical Systems (MCPS) are vul- nerable to accidental or malicious faults that can target their controllers and cause safety hazards and harm to patients. This paper proposes a combined model and data-driven approach for designing context-aware monitors that can detect early signs of hazards and mitigate them in MCPS. We present a framework for formal specification of unsafe system context using Signal Temporal Logic (STL) combined with an optimization method for patient-specific refinement of STL formulas based on real or simulated faulty data from the closed-loop system for the gener- ation of monitor logic. We evaluate our approach in simulation using two state-of-the-art closed-loop Artificial Pancreas Systems (APS). The results show the context-aware monitor achieves up to 1.4 times increase in average hazard prediction accuracy (F1- score) over several baseline monitors, reduces false-positive and false-negative rates, and enables hazard mitigation with a 54% success rate while decreasing the average risk for patients.