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1. Defining and Assessing Systems Thinking in Diverse Engineering Populations

   Mosyjowski, E.A.; Daly, S.R.; Lattuca, L. (January 2019, Proceedings of the American Society for Engineering Education Conference)

   Engineers are called to play an important role in addressing the complex problems of our global society, such as climate change and global health care. In order to adequately address these complex problems, engineers must be able to identify and incorporate into their decision making relevant aspects of systems in which their work is contextualized, a skill often referred to as systems thinking. However, within engineering, research on systems thinking tends to emphasize the ability to recognize potentially relevant constituent elements and parts of an engineering problem, rather than how these constituent elements and parts are embedded in broader economic, sociocultural, and temporal contexts and how all of these must inform decision making about problems and solutions. Additionally, some elements of systems thinking, such as an awareness of a particular sociocultural context or the coordination of work among members of a cross-disciplinary team, are not always recognized as core engineering skills, which alienates those whose strengths and passions are related to, for example, engineering systems that consider and impact social change. Studies show that women and minorities, groups underrepresented within engineering, are drawn to engineering in part for its potential to address important social issues. Emphasizing the importance of systems thinking and developing a more comprehensive definition of systems thinking that includes both constituent parts and contextual elements of a system will help students recognize the relevance and value of these other elements of engineering work and support full participation in engineering by a diverse group of students. We provide an overview of our study, in which we are examining systems thinking across a range of expertise to develop a scenario-based assessment tool that educators and researchers can use to evaluate engineering students’ systems thinking competence. Consistent with the aforementioned need to define and study systems thinking in a comprehensive, inclusive manner, we begin with a definition of systems thinking as a holistic approach to problem solving in which linkages and interactions of the immediate work with constituent parts, the larger sociocultural context, and potential impacts over time are identified and incorporated into decision making. In our study, we seek to address two key questions: 1) How do engineers of different levels of education and experience approach problems that require systems thinking? and 2) How do different types of life, educational, and work experiences relate to individuals’ demonstrated level of expertise in solving systems thinking problems? Our study is comprised of three phases. The first two phases include a semi-structured interview with engineering students and professionals about their experiences solving a problem requiring systems thinking and a think-aloud interview in which participants are asked to talk through how they would approach a given engineering scenario and later reflect on the experiences that inform their thinking. Data from these two phases will be used to develop a written assessment tool, which we will test by administering the written instrument to undergraduate and graduate engineering students in our third study phase. Our paper describes our study design and framing and includes preliminary findings from the first phase of our study. 

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2. Systems Thinking Assessments: Approaches That Examine Engagement in Systems Thinking

   Dugan. K. E., Mosyjowski (January 2021, Proceedings of the 2021 American Society for Engineering Education Annual Conference & Exposition)

   null (Ed.)

   While systems engineers rely on systems thinking skills in their work, given the increasing complexity of modern engineering problems, engineers across disciplines need to be able to engage in systems thinking, including what we term comprehensive systems thinking. Due to the inherent complexity of systems thinking, and more specifically comprehensive systems thinking, it is not easy to know how well students (and practitioners) are learning and leveraging systems thinking approaches. Thus, engineering managers and educators can benefit from systems thinking assessments. A variety of systems thinking assessments exist that are relevant to engineers, including some focused on the demonstration of systems thinking knowledge or skills and others measuring attitudes, interests, or values related to systems thinking. Starting with a collection of systems thinking assessments from a systematic literature review conducted by our team, we analyzed in-depth those behavior-based assessments that included the creation of a visual representation and were open-ended, i.e., it did not presuppose or provide answers. The findings from this in-depth analysis of systems thinking behavior-based assessments identified 1) six visualization types that were leveraged, 2) dimensions of systems thinking that were assessed and 3) tensions between the affordances of different assessments. In addition, we consider the ways assessments can be used. For example, using assessments to provide feedback to students or using assessments to determine which students are meeting defined learning goals. We draw on our findings to highlight opportunities for future comprehensive systems thinking behavior-based assessment development. 

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3. Understanding the Potential of a Holistic Engineering Project Experience in the Advancement of the Professional Formation of Engineers

   Dey, K.; Rahman, M.T.; Pyrialakou, V. D.; Martinelli, D.; Fraustino, J. D.; Deskins, J; Roy, A. R; Rambo-Hernandez, K. (July 2021, 2021 ASEE Virtual Annual Conference & Exposition)

   null (Ed.)

   The role of modern engineers as problem-definer often require collaborating with cross-disciplinary teams of professionals to understand and effectively integrate the role of other disciplines and accelerate innovation. To prepare future engineers for this emerging role, undergraduate engineering students should engage in collaborative and interdisciplinary activities with faculties and students from various disciplines (e.g., engineering and social science). Such cross-disciplinary experiences of undergraduate engineering students are not common in today’s university curriculum. Through a project funded by the division of Engineering Education and Centers (EEC) of the National Science Foundation (NSF), a research team of the West Virginia University developed and offered a Holistic Engineering Project Experience (HEPE) to the engineering students. Holistic engineering is an approach catering to the overall engineering profession, instead of focusing on any distinctive engineering discipline such as electrical, civil, chemical, or mechanical engineering. Holistic Engineering is based upon the fact that the traditional engineering courses do not offer sufficient non-technical skills to the engineering students to work effectively in cross-disciplinary social problems (e.g., development of transportation systems and services). The Holistic Engineering approach enables engineering students to learn non-engineering skills (e.g., strategic communication skills) beyond engineering math and sciences, which play a critical role in solving complex 21st-century engineering problems. The research team offered the HEPE course in Spring 2020 semester, where engineering students collaborated with social science students (i.e., students from economics and strategic communication disciplines) to solve a contemporary, complex, open-ended transportation engineering problem with social consequences. Social science students also received the opportunity to develop a better understanding of technical aspects in science and engineering. The open ended problem presented to the students was to “Restore and Improve Urban Infrastructure” in connection to the future deployment of connected and autonomous vehicles, which is identified as a grand challenge by the National Academy of Engineers (NAE) [1]. 

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4. Computational Thinking in the Formation of Engineers: Year 3

   https://doi.org/10.18260/1-2--36826  

   Mendoza Diaz, Noemi V; Meier, Russ; Trytten, Deborah Anne; Moore, Janie M; Yoon, So Yoon; Hogan, Harry A (June 2023, American Society of Engineering Education Annual Conference & Exposition)

   This project has been dedicated to advance the way computational thinking is taught to engineering undergraduate students with a multitude of social identities. It is an expectation that with the understanding of the multiple factors that affect computational thinking skills development, students succeed in enculturating to the engineering professional practice. During the third year of this project, the first major result is the conclusion of the validation process of the Engineering Computational Thinking Diagnostic (ECTD) making use of exploratory and confirmatory factor analyses (EFA-CFA). Our validation showed that the ECTD questions cluster in one factor, what we call the computational thinking factor for engineers. Other validation statistical processes (i.e. correlations, regressions, ANOVA and t-tests) proved the predictability potential use of this tool in determining how well prepared students arrive to the engineering classroom and how their prior coding experience can determine their success in introductory coding engineering courses. The second major result is the revelation that the inequities caused by the many forms of privilege that some engineering students benefit from are being exacerbated by the integration of computational thinking into introductory engineering classes. Due to pandemic-related challenges in recruiting a representative sample of participants, the majority of the self-selected participants in our research identify with groups with disproportionately large participation in engineering (specifically White and Asian) and are academically successful in engineering. To respond to this challenge we are seeking to broaden our perspective by seeking participants with failing grades for a final round of data collection, although we are well aware that students in this group are often reluctant to participate in research. The fourth and last major result is related to the position of stress versus Artificial Intelligence (AI) perceptions, both part of the ECTD instrument. The position of stress questions involved perceived difficulty and confidence level after taking the ECTD. The artificial intelligence question asked the perceived impact of AI in students’ future career prospects. Preliminary analysis is suggesting that confidence level is correlated with AI positive perceptions. Although not part of the original NSF grant, we considered AI the natural evolution of computational thinking in the formation of engineers and plan to continue our work in this direction. 

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5. Computational Thinking in the Formation of Engineers (Year 1)

   Mendoza Diaz, Noemi V.; Meier, Russ; Trytten, Deborah A.; Yoon, So Yoon; Moore, Janie M.; Ogilvie, Andrea M.; Weichold, Mark (January 2021, 2021 ASEE Annual Conference & Exposition)

   null (Ed.)

   Computational thinking is understood as the development of skills and knowledge in how to apply computers and technology to systematically solve problems. Computational thinking has been acknowledged as one key aspect in the taxonomy of engineering education and implied in multiple ABET student outcomes. Moreover, many introductory engineering courses worldwide have a component of programming or computational thinking. A preliminary study of enculturation to the engineering profession found that computational thinking was deemed a critical area of development at the early stages of instruction. No existing computational thinking framework was found to fully meet the needs of engineers, based on the expertise of researchers at three different institutions and the aid of a comprehensive literature review. As a result, a revised version of a computational thinking diagnostic was developed and renamed the engineering computational thinking diagnostic (ECTD). The five computational thinking factors of the ECTD are (1) Abstraction, (2) Algorithmic Thinking and Programming, (3) Data Representation, Organization, and Analysis, (4) Decomposition, and (5) Impact of Computing. This paper describes the development and revisions made to the ECTD using data collected from first-year engineering students at a Southwestern public university. The goal of the development of the ECTD is to capture the entry and exit skill levels of engineering students in an engineering program. 

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