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

Abstract

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.

Computational thinking in higher education: A review of the literature

“…The models and modeling perspective has been heavily studied concerning engineering education [7,8,33]. Discipline-based modeling and simulation has been shown to help students build both programming skills and disciplinary skills within engineering contexts [24,28,31] Thus, bringing this perspective to incorporating computational thinking within education engineering contexts may give key insights into how best to create computational thinking-enabled engineering professionals.…”

Computational apprenticeship: Cognitive apprenticeship for the digital era

“…Qualitative analysis of the students' problem-solving process as described in the interviews resulted in an outcome space of four predominant archetypes of behavior. Findings from our study identified four categories of description; two for the cognitive dimension and two for the metacognitive dimension (Magana, Fennell, Vieira, & Falk, 2019). To summarize briefly, in the cognitive dimension, the two main approaches that students adopted were implementation-oriented and knowledge-oriented.…”

Students’ Approaches to Studying through a Situative Lens

“…Drawing from Magana et al (2019), who also used thematic analysis within a phenomenological methodological framework (see also Daly et al, 2012), our analysis consists of the following steps: (1) use thematic analysis to construct a limited number of qualitatively different themes that describe the ways students experience school that lead to rote or to conceptual learning operations; (2) identify the central aspects of these themes including their frequency and affect;…”