A case study of undergraduate engineering students' computational literacy and self-beliefs about computing in the context of authentic practices

Magana, Alejandra J.; Falk, Michael L.; Vieira, Camilo; Reese, Michael J.

doi:10.1016/j.chb.2016.03.025

Cited by 45 publications

(30 citation statements)

References 38 publications

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“…If these challenges pose difficulties in introducing new knowledge and skills such as modeling and simulation, the strategies that emerged from the experts’ responses also help engineering educators to address these issues without losses in curriculum content or need of additional credit hours. Some documented effective strategies for integrating computational tools and methods in the curriculum are by aligning modeling and simulation practices with (1) laboratory sessions , (2) introductory programming courses for science and engineering majors , (3) computational modules embedded as projects or homework assignments as part of the overall curriculum [30,31], (4) specific courses in computational science and engineering , and (5) problem‐based learning scenarios vertically integrated that link across courses , among others.…”

Section: Discussionmentioning

confidence: 99%

Modeling and simulation practices for a computational thinking‐enabled engineering workforce

Magana

Coutinho

2016

Comp Applic In Engineering

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Computational thinking has been recognized as a collection of understandings and skills required for new generations of students not only proficient at using tools, but also at creating them and understanding the implication of their capabilities and limitations. This study proposes the combination of modeling and simulation practices along with disciplinary learning as a way to synergistically integrate and take advantage of computational thinking in engineering education. This paper first proposes a framework that identifies different audiences of computing and related computational thinking practices at the intersection of computer science and engineering. Then, based on a survey with 37 experts from industry and academia, this paper also suggests a series of modeling and simulation practices, methods, and tools for such audiences. Finally, this paper also reports experts' identified challenges and opportunities for integrating modeling and simulation practices at the undergraduate level. ß 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ 25:62-78, 2017; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21779

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Section: Discussionmentioning

confidence: 99%

Modeling and simulation practices for a computational thinking‐enabled engineering workforce

Magana

Coutinho

2016

Comp Applic In Engineering

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“…The obstacles identified have primarily been related to students' inability to map the relationships among the physical phenomena, the mathematical representation, and the computational representation (Magana et al, , ). However, when thoughtfully exposed to modeling and simulation practices more intensively (e.g., for a semester‐long term), undergraduate students have demonstrated their ability to acquire foundational computing concepts and procedures for solving well‐structured engineering problems (Magana, Falk, & Reese, ; Magana, Falk, Vieira, & Reese, ).…”

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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“…Pioneering work from Hutchison, Follman, Sumpter, and Bodner () suggests that self‐efficacy in computing among women students may be a valuable focus for intervention. We believe that constructivist approaches for early and consistent exposure to computation can promote positive self‐belief (Magana et al, ). Furthermore, the use of cognitive apprenticeship within computing courses has been shown to significantly reduce dropout rates (Vihavainen, Paksula, & Luukkainen, ).…”

Section: New Research Directionsmentioning

confidence: 99%

Toward computational apprenticeship: Bringing a constructivist agenda to computational pedagogy

Fennell

Lyon

Madamanchi

et al. 2020

J of Engineering Edu

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A case study of undergraduate engineering students' computational literacy and self-beliefs about computing in the context of authentic practices

Cited by 45 publications

References 38 publications

Modeling and simulation practices for a computational thinking‐enabled engineering workforce

Modeling and simulation practices for a computational thinking‐enabled engineering workforce

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

Toward computational apprenticeship: Bringing a constructivist agenda to computational pedagogy

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