An Exploratory Study of the Role of Modeling and Simulation in Supporting or Hindering Engineering Students’ Problem-solving Skills

Shaikh, Uzma; Vieira, Camilo; Garcı́a, R. Edwin; Magana, Alejandra J.

doi:10.18260/p.23524

Cited by 1 publication

(1 citation statement)

References 23 publications

(25 reference statements)

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“…Students were given extended periods of time to complete each project, allowing plenty of time for students to seek help from the instructional staff when they were stuck. • Sequencing: Implemented by following the problem solving process as steps for guiding the modeling and simulation process (Fennell, Coutinho, Magana, D, & Zavattieri, 2017;Alejandra J Magana et al, 2016;Shaikh, Magana, Vieira, & Garcia, 2015). • Sociology: Utilizing anchored instruction by contextualizing the learning experiences within authentic tasks, which occur in real-life contexts and establish meaningful associations between learning experiences and among the knowledge, skills, and practices of a discipline (Choi & Hannafin, 1995;.…”

Section: Learning Strategiesmentioning

confidence: 99%

Computational apprenticeship: Cognitive apprenticeship for the digital era

Fennell¹,

Lyon²,

Madamanchi³

et al. 2019

Preprint

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The conceptualization of Computational Thinking as a cross-cutting skill with relevance across disciplines has ushered in wide-ranging efforts to increase computational education in all facets of education. However, the majority of initiatives for integrated computing education have focused on K-12 settings, as has most education research around computational thinking. At the postsecondary level, computing education remains largely siloed within specific programming courses and has not been well-integrated throughout the STEM curriculum. Current instructional approaches often leave students poorly prepared to transfer their computing knowledge to solve new real-world problems. Additionally, there is limited education research into how best to develop computational thinking among postsecondary students. In fact, education research into computational thinking remains undertheorized and is often definitional in nature. Here, we integrate computational thinking with the educational psychology concept of adaptive expertise. Finally, we contextualize computational thinking within constructivist learning theories by introducing computational apprenticeship, an application of cognitive apprenticeship to computing. Computational apprenticeship provides a research and practice model for supporting the development of computational adaptive expertise.

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Section: Learning Strategiesmentioning

confidence: 99%