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1. Robots for Social Justice (R4SJ): Toward a More Equitable Practice of Human-Robot Interaction

   Zhu, Yifei; Wen, Ruchen; Williams, Tom (March 2024, ACM/IEEE International Conference on Human-Robot Interaction)

   In this work, we present Robots for Social Justice (R4SJ): a framework for an equitable engineering practice of Human-Robot Interaction, grounded in the Engineering for Social Justice (E4SJ) framework for Engineering Education and intended to complement existing frameworks for guiding equitable HRI research. To understand the new insights this framework could provide to the field of HRI, we analyze the past decade of papers published at the ACM/IEEE International Conference on Human-Robot Interaction, and examine how well current HRI research aligns with the principles espoused in the E4SJ framework. Based on the gaps identified through this analysis, we make five concrete recommendations, and highlight key questions that can guide the introspection for engineers, designers, and researchers. We believe these considerations are a necessary step not only to ensure that our engineering education efforts encourage students to engage in equitable and societally beneficial engineering practices (the purpose of E4SJ), but also to ensure that the technical advances we present at conferences like HRI promise true advances to society, and not just to fellow researchers and engineers. 

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2. Robots for Social Justice (R4SJ): Toward a More Equitable Practice of Human-Robot Interaction

   https://doi.org/10.1145/3610977.3634944  

   Zhu, Yifei; Wen, Ruchen; Williams, Tom (March 2024, ACM)

   In this work, we present Robots for Social Justice (R4SJ): a framework for an equitable engineering practice of Human-Robot Interaction, grounded in the Engineering for Social Justice (E4SJ) framework for Engineering Education and intended to complement existing frameworks for guiding equitable HRI research. To understand the new insights this framework could provide to the feld of HRI, we analyze the past decade of papers published at the ACM/IEEE International Conference on Human-Robot Interaction, and examine how well current HRI research aligns with the principles espoused in the E4SJ framework. Based on the gaps identifed through this analysis, we make fve concrete recommendations, and highlight key questions that can guide the introspection for engineers, designers, and researchers. We believe these considerations are a necessary step not only to ensure that our engineering education eforts encourage students to engage in equitable and societally benefcial engineering practices (the purpose of E4SJ), but also to ensure that the technical advances we present at conferences like HRI promise true advances to society, and not just to fellow researchers and engineers. 

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3. Lessons Learned from Teaching Culturally Relevant Engineering Design in K–12 Classrooms and Applying Them to Undergraduate Engineering Courses

   Klemetsrud, BJ; Bowman, FM (June 2023, 2023 ASEE Annual Conference & Exposition)

   When confronted with systematic racism, social justice, and equity issues, engineering and STEM education often assumes that these topics will be covered in other courses and are not relevant to STEM. However, engineering as a discipline has one of the greatest effects on society’s well-being. From the raw materials used, products created, and emissions generated, all aspects of engineering have direct and indirect impacts on humanity. Our current engineering education project works with upper elementary and middle school teachers to apply a culturally relevant engineering design (CRED) framework within their classrooms. This framework is adapted from UTeachEngineering and culturally relevant pedagogy from Gay and Billings is embedded within each step of the design process. The North Dakota Native American Essential Understandings are used to frame and inform the culturally relevant pedagogy. Tribal elder’s stories and experiences are centered along with community leaders in each of the school’s communities. Responses from students and teachers has been overwhelmingly positive. Teachers have noticed increased engagement from all students when cultural and community leaders have been invited into the classroom and involved in the engineering design process. Students who normally do not see themselves represented in STEM professions have taken active leadership roles in their group’s engineering design process. Teachers have also recognized that culturally relevant pedagogy can be utilized in all aspects of their curricula. With the success of the project in elementary and middle school classrooms, the question then became, how can we see similar success in our college classrooms? When brainstorming how to incorporate culture and community in our curricula it became apparent that best practices in engineering education have the opportunity to intentionally involve community and cultural leaders. ABET learning outcomes require the “consideration of public health, safety, and welfare” in engineering design and “the impact of engineering solutions in global, economic, environmental, and societal contexts.” When making engineering design decisions, who will be affected if there is an accidental release of chemicals to the environment? Which communities are affected by global warming? Will the public be able to afford the new product that is being produced? Will the new processes or products add value to people’s lives? And how do we train future engineers to consider all community members, not just those who look like them, but those from the most marginalized groups? This talk will introduce our culturally relevant engineering design framework, provide ways to include community and cultural leaders within courses, and how, with the help of Northwestern’s Anti-Racism, Diversity, Equity and Inclusion resources, to create homework problems that reflect social justice and equity issues within engineering 

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4. How Modeling the Adoption of Household Clean Energy Technologies can Inform Stakeholder Decisions

   https://doi.org/10.1109/GHTC46280.2020.9342936  

   Peiffer, Erin; MacCarty, Nordica (October 2020, 2020 IEEE Global Humanitarian Technology Conference (GHTC))

   null (Ed.)

   Increasing the adoption of household clean energy technologies is important to achieving sustainable development and to improving the environmental, economic, and social impacts of these technology interventions. While much work has been done to understand the many factors driving successful interventions, little research has been done to quantify and then model the adoption of these technologies. Current optimization models to maximize impact rely on the effective prediction of adoption, yet this piece remains the least understood component. The purpose of this paper is to outline the various ways in which being able to model the adoption of household clean energy technologies would be beneficial for designers, implementation organizations, and policymakers to aid in their design and decision-making processes. We provide a brief review of the literature and current challenges to adoption, examples of current methods and modeling tools that can be used to optimize sustainable impacts, and how these tools could be improved through adoption modeling. We discuss the benefits of being able to model adoption for various stakeholders in the clean energy sector along with proposing some methodologies that can be used to accomplish this goal. 

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5. Model based systems engineering—A text mining based structured comprehensive overview

   https://doi.org/10.1002/sys.21601  

   Akundi, Aditya; Mondragon, Oscar (September 2021, Systems Engineering)

   null (Ed.)

   An observed increase in systems scale and complexity has led to a significant momentum in exploring, identifying, and adopting model based systems engineering (MBSE) tools and techniques amongst research communities and industry practitioners. Several attempts to transform systems design and engineering practices through the use of MBSE in academia and industry has led to a considerable increase in the number of articles published containing the keyword “MBSE.” This growth serves as the motivation in this paper to explore the MBSE landscape with the help of text mining techniques to identify the most often used key terms, tools, and languages, in the context of research in MBSE and the thematic aspects defining the use of MBSE by researchers and practitioners. The objective of this paper is to provide a structured comprehensive overview of research contributions across the MBSE landscape by employing text mining techniques for: (a) identifying the concepts and methodologies inferred upon in relation to MBSE, and (b) classifying the literature published to identify commonalities across academic researchers and practitioners using MBSE tools and methods. For this purpose, the abstracts of 2380 relevant articles published in the period of the last two decades from five different databases are mined. It is found that the terms “SysML,” “Cyber Physical Systems,” and “Production” are the most used terms among researchers across the MBSE landscape with SysML being the most widely used modeling language. Further, six major thematic topics are identified that classify articles from over the last two decades with an increasing interest observed in the use of MBSE to support manufacturing and production engineering activities, especially in the cyber physical systems domain. The contributions of this paper provide a leeway on using text mining techniques to understand the research directions that are currently of interest in the field of MBSE and thereby identify potential future research directions. 

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