Cognitive styles in design problem solving: Insights from network-based cognitive maps

Kim, eunjin; KwanMyung, Kim

doi:10.1016/j.destud.2015.05.002

Cited by 34 publications

(26 citation statements)

References 74 publications

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“…Network analysis has also been useful for understanding smaller, real-life designer networks in conjunction with protocol studies. For instance, network analysis tools has been used to visualize designer activities (Cash et al, 2014) , derive cognitive maps to illustrate the evolution of concepts and ideas (Kim and Kim, 2015), and design collaborative services to foster community resilience (Baek et al, 2015).…”

Section: Background and Related Workmentioning

confidence: 99%

Collective design in 3D printing: A large scale empirical study of designs, designers and evolution

Özkil

2017

Design Studies

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Section: Background and Related Workmentioning

confidence: 99%

Collective design in 3D printing: A large scale empirical study of designs, designers and evolution

Özkil

2017

Design Studies

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“…In order to be successful on such a task, students must know how to set reasonable goals for themselves and adopt intrinsic standards for success so that they will be able to solve problems strategically. Many studies (Atman et al, 2007(Atman et al, , 2005(Atman et al, , 1999Cardella, Atman, & Adams, 2006;Cross, 2000;Dym & Little, 2008;Jonassen, Strobel, & Lee, 2006;Kim & Kim, 2015;Lawanto & Santoso, 2014;Lee & Johnson-Laird, 2013;Sobek & Jain, 2007) have found that students' cognitive and metacognitive skills (i.e., monitoring and controlling one's cognitive processes) play an essential role in problem-solving processes, particularly in solving ill-structured problems such as design. In other words, engineering design tasks require effective forms of SR.…”

Section: Cognitive Strategies In Engineering Designmentioning

confidence: 99%

Self-Regulation Strategies in an Engineering Design Project

Lawanto¹,

Febrian²,

Butler³

et al. 2019

IES

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Models of self-regulation describe how individuals engage deliberately and reflectively in goal-directed action in order to achieve valued goals. Studies have found that the consistent use of self-regulation in an academic setting is highly correlated with student achievement. Self-regulation plays a critical role in problem-solving, particularly when unraveling ill-structured problems as is required in engineering design. The primary research question: How did engineering students perceive their self-regulation activities while engaged in a design project? A total of 307 students from three higher education institutions working on their capstone engineering design projects participated in the study. The study evaluated students’ self-regulation in relation to both design and project management skills. We used a self-regulation in engineering design questionnaire (EDMQ) to assess students’ approaches to self-regulation. Quantitative data were analyzed in two parts using descriptive and inferential statistics. Findings suggested that: (1) Students focused more consistently on task interpretation than other self-regulatory strategies, particularly during design; (2) Students lacked awareness of the essential need to develop a method to assess the design deliverables; (3) Self-regulation gaps were found during early design phases, but as the design process progressed, a more balanced approach to self-regulation was apparent. Given the importance of task interpretation to successful performance, students attended to identifying tasks during both the design process and project management. However, they did not report engaging in planning, implementing, and monitoring and fix-up strategies as consistently, even when those processes were relevant and called for. Implications are drawn for research, theory, and practice.

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“…Understanding a problem is the first critical step leading to strategies to achieve the solution. Problem definition is always the first step in any model for problem-solving process (Jonassen, 2004;Kim & Kim, 2015;Koichu & Leron, 2015;Polya, 1957). However, successful problem definition requires a strategy to understand the problem.…”

Section: Introductionmentioning

confidence: 99%

Students’ Task Understanding during Engineering Problem Solving in an Introductory Thermodynamics Course

Lawanto¹,

Minichiello²,

Uziak³

et al. 2018

IES

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Understanding problems or tasks is a critical step in any problem-solving activity and the heart of self-regulated learning. When encountering a problem, students draw upon information available in the environment, along with knowledge, concepts, and perceptions derived from prior learning experiences, to interpret the demands of the task. Interpretation of tasks is, therefore, a key determinant of the goals set while learning, strategies selected to achieve those goals, and the criteria used to self-assess and evaluate outcomes. The purpose of this study is to better understand engineering students’ self-regulation in task interpretation processes while engaged in problem solving in an introductory engineering thermodynamics course. Two research questions guided the study: (1) What are the gaps, if any, between the instructor’s and students’ interpretation (explicit and implicit task features) of a problem-solving task?; and (2) How do students’ task interpretation (explicit and implicit) change after engaging in self-evaluation of their problem-solving processes? One hundred twelve (112) second year engineering undergraduates voluntarily participated in the study. Analysis of the data collected revealed a significant difference between the instructor’s and students’ task interpretation of the assigned problems. Furthermore, the analysis showed that students’ had a higher ability to identify the explicit parts of problem tasks than implicit ones. Students were able to grasp 63 to 77 percent and 39 to 49 percent, respectively, of the explicit and implicit information that was presented to them while engaged in problem-solving activities.

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Cognitive styles in design problem solving: Insights from network-based cognitive maps

Cited by 34 publications

References 74 publications

Collective design in 3D printing: A large scale empirical study of designs, designers and evolution

Collective design in 3D printing: A large scale empirical study of designs, designers and evolution

Self-Regulation Strategies in an Engineering Design Project

Students’ Task Understanding during Engineering Problem Solving in an Introductory Thermodynamics Course

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