Modeling and Simulation in Engineering Education: A Learning Progression

Magana, Alejandra J.

doi:10.1061/(asce)ei.1943-5541.0000338

Cited by 39 publications

(32 citation statements)

References 31 publications

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“…With the diverse nature of definitions and assessment of computational thinking, the nature of the relationship between computation and computational thinking can feel murky at best. Research in engineering education should aim to operationalize computational thinking, and help to better structure discipline-based computing which is vital to the field of engineering [25][26][27]. Additionally, engineering educators should further investigate how computational thinking can be taught to not further, but address prevalent socioeconomic, race, and gender gaps in the field [1,12,36].…”

Section: Implications For the Field Of Engineering Educationmentioning

confidence: 99%

Computational thinking in higher education: A review of the literature

Lyon

Magana

2020

Comp Applic In Engineering

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Computational thinking is of growing interest to the science, technology, engineering, and mathematics (STEM) education research community. Calls from national agencies look to increase computation in STEM education. This review identifies key areas for future study by reviewing recent empirical studies that investigate computational thinking in teaching and learning contexts within higher education. Using a systematic process, this review identified four different databases for peer‐reviewed research articles using keywords. Results were evaluated against inclusion and exclusion criteria. Studies were analyzed for types of methods, target population, the role of computational thinking, pedagogical designs used, and significant findings of the study. This process resulted in a final set of 13 studies. The results indicate that computational thinking research in higher education is growing, yet there are opportunities for more research. The findings of this study highlight the need for more concrete definitions and implementations of computational thinking within higher education spaces.

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Section: Implications For the Field Of Engineering Educationmentioning

confidence: 99%

Computational thinking in higher education: A review of the literature

Lyon

Magana

2020

Comp Applic In Engineering

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“…Specifically, employers from various engineering sectors value students' abilities to “understand engineering principles and computational principles that allow them to use computational tools to solve engineering problems by moving between physical systems and abstractions in software” (Vergara et al, , p. 6). Similarly, engineering education policymakers and the engineering education research community have recommended the incorporation of modeling and simulation skills into the undergraduate engineering curriculum (Magana, ; Magana & Coutinho, ). For instance, the Transforming Undergraduate Education in Engineering Report (American Society for Engineering Education, ), recently identified that industry professionals value programming skills and the ability to use computational tools to support problem‐solving.…”

Section: Introductionmentioning

confidence: 99%

Characterizing the interplay of cognitive and metacognitive knowledge in computational modeling and simulation practices

Magana

Fennell

Vieira

et al. 2019

J of Engineering Edu

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Background Modeling and simulation practices have become commonplace in modern engineering, but in‐depth research on the development of modeling and simulation expertise is needed to identify the learning processes involved in successfully acquiring these skills. Purpose This study investigated student dimensions of expertise when engaged in modeling and simulation practices. The guiding research question was “How do students use cognitive and metacognitive knowledge when engaged with computational modeling and simulation practices?” Design/Method This study included 11 undergraduate engineering students enrolled in a course on computational materials science. Data were collected from one of five computational challenges administered during the course. Students' cognitive and metacognitive knowledge use was first analyzed using thematic analysis and then through a phenomenographic approach. Findings were interpreted using the lens of adaptive expertise. Results Results describe how students used their cognitive and metacognitive knowledge to approach the computational challenge. Two categories in the cognitive dimension were identified: implementation‐oriented and knowledge‐oriented. Two categories identified in the metacognitive dimension were plan‐oriented and action‐oriented approaches. These categories are further presented as an outcome space by aligning them with the dimensions of adaptive expertise. Conclusions Results indicated that students in the action/implementation‐oriented category exhibited many of the qualities expected of inexperienced novices, while students in the plan/knowledge‐oriented category demonstrated more of the qualities expected of adaptive experts. However, results were less conclusive for students in the two intermediate thematic categories, who often exhibited some but not all of the qualities of both novices and experts.

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“…As it is well-known, computer-based modeling environments can supply students with effective pedagogical strategies dealing with complex real-world systems and everyday problem solutions [1,3,6,10,19]. Research has shown that computer simulations can efficiently raise student's interest in learning by vivid graphical construction and animation [12,24] and be used to help students to gain insights into phenomena and overcome mathematical difficulties [14].…”

Section: Introductionmentioning

confidence: 99%

Computer simulations to approach surface tension by means of a simple mesoscopic mechanical model

Battaglia

Gallitto

Fazio

2019

Comp Applic In Engineering

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A small insect can stand or walk on water surface, drops of mercury do not spread on a solid surface, and a meniscus is formed at the free surface of a liquid contained in a thin vessel. These phenomena can be seen as macroscopic manifestations of molecular interactions and can be explained macroscopically in terms of surface tension. In this study, we deal with an approach to surface tension from a mechanical point of view, presenting a simple mesoscopic mechanical model of surface tension and the results of its implementation in numerical fluid dynamics simulations. Particularly, phenomena like droplet formation without gravity and with gravity when it can drop from a narrow hole like a trickling tap, the formation of a meniscus at the free surface of a liquid contained in a vessel, the behavior of a small piece of solid on a liquid surface, and a sessile droplet are studied. Student and teachers can study the behavior of a liquid due to the surface tension by using the numeric simulations as a “tool” for analyzing several different situations.

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Modeling and Simulation in Engineering Education: A Learning Progression

Cited by 39 publications

References 31 publications

Computational thinking in higher education: A review of the literature

Computational thinking in higher education: A review of the literature

Characterizing the interplay of cognitive and metacognitive knowledge in computational modeling and simulation practices

Computer simulations to approach surface tension by means of a simple mesoscopic mechanical model

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