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1. Cultural Context in Engineering Design: Exploring the Influence of Communication on Design Practices

   https://doi.org/10.1115/1.4068593  

   Marshall, Avery; Fu, Katherine (December 2025, Journal of Mechanical Design)

   Just as engineering designs can be uniquely created for different cultures around the world, engineers come from all over and view design through their own cultural lenses. Culture can impact how designers perceive themselves, their self-efficacy, and the way they interpret the design task at hand. Studies have shown that cultural values and behavior (i.e., cultural context) impact communication patterns, as well as learning strategies (Newman et al., 2017, “Psychological Safety: A Systematic Review of the Literature,” Hum. Resour. Manage. Rev., 27(3), pp. 521–535. 10.1016/j.hrmr.2017.01.001; Hirsch et al., 2001, “Engineering Design and Communication: The Case for Interdisciplinary Collaboration,” Int. J. Eng. Educ., 17(4/5), pp. 343–348). Halls' information processing continuum illuminates how some cultures communicate explicitly through written and spoken words (low context), while others communicate with a common awareness of nonverbal cues (high context) (Handford et al., 2019, “Which ‘Culture’? A Critical Analysis of Intercultural Communication in Engineering Education,” J. Eng. Educ., 108(2), pp. 161–177. 10.1002/jee.20254). Designers from low-context cultures are more comfortable in a low-context learning environment (e.g., with explicitly written instructions), whereas those from high-context cultures benefit more from face-to-face interactions (Goel and Pirolli, 1992, “The Structure of Design Problem Spaces,” Cogn. Sci., 16(3), pp. 395–429. 10.1207/s15516709cog1603_3). These communication differences impact cross-cultural collaboration within global companies and virtual teams. This study examined whether communicating a design task in a more engaging manner would impact solution quality and self-efficacy, particularly in light of the designer's culture and/or familiarity with the design problem. Engineering undergraduate students and professionals were recruited from each of 10 countries, including the United States, to complete a design task and respond to self-perception questions. Participants were presented with the design problem in one of two modes: written (low context) or video (high context). Results showed that delivery modality and cultural context did impact design solution quality and self-efficacy; however, differences were found between professionals and students. 

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2. Multilevel Decision Support Framework for the Simultaneous Design Exploration of Material Structures and Processes

   https://doi.org/10.1115/DETC2024-146330  

   Digonta, H_M_Dilshad Alam; Nellippallil, Anand Balu; Baby, Mathew (August 2024, American Society of Mechanical Engineers)

   Abstract Traditional manufacturing, such as steel manufacturing, involves a series of processes to realize the final product. The properties and performance of the final product depend on the material processing history and the microstructure generated at each of the processes. Realizing target product performance requires the simultaneous design exploration of the material microstructure and processing, taking into account the multilevel interactions between the material, product, and manufacturing processes. This demands the capability to co-design, which involves sharing a ranged set of solutions through design exploration across multilevel and providing design decision support. In this paper, we present a co-design exploration framework for multilevel decision support. Using the framework, we model the interactions and couplings between the levels and facilitate simultaneous decision-based design exploration. The framework integrates the coupled compromise Decision Support Problem (c-cDSP) construct with interpretable Self-Organizing Maps (iSOM) to facilitate (i) the formulation of the multilevel decision support problems taking into account the interactions and couplings between levels, (ii) the simultaneous visualization and exploration of the multilevel design spaces, and (iii) decision-making across levels for multilevel designers. The efficacy of the framework is tested using a hot rod rolling problem focusing on the interactions between the dynamic and metadynamic phases of material recrystallization and the thermo-mechanical processing during the hot rolling process. The framework is generic and supports the co-design exploration of systems characterized by multilevel interactions, couplings, and multidisciplinary designers. 

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3. A Framework for the Simultaneous Multilevel Design Exploration and Decision Support of Material Structures and Manufacturing Processes

   https://doi.org/10.1115/1.4067844  

   Digonta, H_M_Dilshad Alam; Baby, Mathew; Nellippallil, Anand Balu (April 2025, Journal of Computing and Information Science in Engineering)

   Abstract Traditional manufacturing, such as steel manufacturing, involves a series of processes to realize the final product. The properties and performance of the final product depend on the material processing history and the microstructure generated at each of the processes. Realizing target product performance requires the simultaneous design exploration of the material microstructure and processing, taking into account the multilevel interactions between the material, product, and manufacturing processes. This demands the capability to co-design, which involves sharing a ranged set of solutions through design exploration across multilevel and providing design decision support. In this paper, we present a co-design exploration framework for multilevel decision support. Using the framework, we model the interactions and couplings between the levels and facilitate simultaneous decision-based design exploration. The framework integrates the coupled compromise decision support problem construct with interpretable self-organizing maps to facilitate (i) the formulation of the multilevel decision support problems taking into account the interactions and couplings between levels, (ii) the simultaneous visualization and exploration of the multilevel design spaces, and (iii) decision-making across levels for multilevel designers. The efficacy of the framework is tested using a hot rod rolling problem focusing on the interactions between the dynamic and metadynamic phases of material recrystallization and the thermo-mechanical processing during the hot rolling process. The framework is generic and supports the co-design exploration of systems characterized by multilevel interactions, couplings, and multidisciplinary designers. 

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4. Promoting Computational Thinking in Integrated Engineering Design and Physics Labs

   Lopez-Parra, R. D.; Subramaniam, R. C.; Morphew, J. W. (January 2023, ASEE Annual Conference & Exposition Proceedings)

   Computational thinking has widely been recognized as a crucial skill for engineers engaged in problem-solving. Multidisciplinary learning environments such as integrated STEM courses are powerful spaces where computational thinking skills can be cultivated. However, it is not clear the best ways to integrate computational thinking instruction or how students develop computational thinking in those spaces. Thus, we wonder: To what extent does engaging students in integrated engineering design and physics labs impact their development of computational thinking? We have incorporated engineering design within a traditional introductory calculus-based physics lab to promote students’ conceptual understanding of physics while fostering scientific inquiry, mathematical modeling, engineering design, and computational thinking. Using a generic qualitative research approach, we explored the development of computational thinking for six teams when completing an engineering design challenge to propose an algorithm to remotely control an autonomous guided vehicle throughout a warehouse. Across five consecutive lab sessions, teams represented their algorithms using a flowchart, completing four iterations of their initial flowchart. 24 flowcharts were open coded for evidence of four computational thinking facets: decomposition, abstraction, algorithms, and debugging. Our results suggest that students’ initial flowcharts focused on decomposing the problem and abstracting aspects that teams initially found to be more relevant. After each iteration, teams refined their flowcharts using pattern recognition, algorithm design, efficiency, and debugging. The teams would benefit from having more feedback about their understanding of the problem, the relevant physics concepts, and the logic and efficiency of the flowcharts 

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5. Creation and Characterization of Design Spaces

   Gero, John S; Milovanovic, Julie (July 2022, DRS)

   Lockton, Dan; Lenzi, Sara (Ed.)

   Designers advance in the design processes by creating and expanding the design space where the solution they develop unfolds. This process requires the co- evolution of the problem and the solution spaces through design state changes. In this paper, we provide a methodology to capture how designers create, structure and expand their design space across time. Design verbalizations from a team of three professional engineers are coded into design elements from the Function-Behavior- Structure ontology to identify the characteristics of design state changes. Three types of changes can occur: a change within the problem space, a change within the solution space or a change between the problem and the solution spaces or inversely. The paper explores how to represent such changes by generating a network of design concepts. By tracking the evolution of the design space over time, we represent how the design space expands as the design activity progresses. 

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