Model-Based Systems Thinking: Assessing Engineering Student Teams

Lavi, Rea; Dori, Yehudit Judy; Wengrowicz, Niva; Dori, Dov

doi:10.1109/te.2019.2948807

Cited by 23 publications

(40 citation statements)

References 28 publications

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“…Nineteen assessments focused on knowledge or skill(s) based on performance on a specific task, such as drawing or answering open-ended, fill-in-the-blank or multiplechoice questions. For example, the Systems Thinking Assessment Rubric (STAR) had teams create conceptual models of a selected system and these models were then scored based on how fully they communicated an understanding of each of nine attributes, with one such attribute being the complexity levels of the model (Lavi et al, 2020(Lavi et al, , 2021.…”

Section: Behavior Basedmentioning

confidence: 99%

Systems thinking assessments in engineering: A systematic literature review

et al. 2021

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Engineers, facing increasingly complex problems, need to understand the technical and contextual aspects of their work to develop effective solutions. Assessments of comprehensive systems thinking skills are needed to support the development of these skills and to inform professional placement. Thus, our study investigated current systems thinking assessments in engineering by systematically reviewing existing assessments. We analyzed which systems thinking skills were emphasized, how they were evaluated, how data were collected and in what content areas assessments were based. The results revealed a range of assessments, in terms of type, format, and content area, but a lack of assessments that equally prioritized accounting for technical and contextual considerations. This overview of assessments can be used by employers and educators to select assessments appropriate for their contexts and goals. Overall, this study demonstrates a need for comprehensive systems thinking assessments that evaluate performance.

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Section: Behavior Basedmentioning

confidence: 99%

Systems thinking assessments in engineering: A systematic literature review

et al. 2021

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“…However, while privacy protecting holds many benefits, it may also encapsulate some costs. These costs are not considered in current methods for evaluating systems thinking skills, which are focused more on identifying the cornerstones of these traits, for example, the four factors of the DSRP theory [27], or the classification of systems thinking attributes into system function [35]. This study, however, addresses the cost of biasing an assessment process, and seeks to minimize it.…”

Section: Discussionmentioning

confidence: 99%

“…Another approach seeks to define the complete set of skills required for systems thinking, e.g., the use of mental modeling and abstraction, and by quantitative assessment of these skills the systems thinking trait may be evaluated [34]. Lavi et al [35] classified systems thinking attributes into system function, structure, and behavior, and by scoring proposed system models based on object-process methodology they evaluated systems thinking skills. Buckle [36] examined the utilization of a maturity model to assess the competence of a person to handle complex systems, i.e., systems thinking skills (coined as MMSTC-Maturity Model of Systems Thinking Competence).…”

Section: Introductionmentioning

confidence: 99%

Introducing the Privacy Aspect to Systems Thinking Assessment Method

Hirschprung

Kordova

2021

Systems

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Systems thinking is a valuable skill that may be required for an individual to be promoted in the business arena to managerial or leading positions. Thus, assessing systems thinking skills is an essential transaction for decision makers in the organization as a preceding step to the promotion decision. One of the well-known and validated tools for this task is a questionnaire. However, because some of the questions invade the employee or candidate’s privacy, the answer may be biased. In this paper, we consider this potential bias, a phenomenon that is becoming more and more significant as privacy concerns and awareness continuously increase in the modern digital world. We propose a formal methodology to optimize the questionnaire based on the privacy sensitivity of each question, thereby providing a more reliable assessment. We conducted an empirical study (n=142) and showed that a systems skills questionnaire can be enhanced. This research makes a significant contribution to improving the systems skills assessment process in particular, and lays the foundations for improving the evaluation of other skills or traits.

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“…In the general system theory, von Bertalanffy (1968) derived the idea of systems thinking from many different fields, including systems in natural and social sciences, by seeing the commonality in methodological thinking. Given this broad definition of systems thinking, research in science education has identified many different types of thinking processes that fall under the umbrella of systems thinking, such as thinking in levels (Boersma et al, 2011; Wilensky & Resnick, 1999), causal reasoning (Hmelo‐Silver et al, 2000; Jacobson & Wilensky, 2006), mechanistic reasoning (Hmelo‐Silver et al, 2017; Krist et al, 2019; Russ et al, 2008), structure–function‐behavior (Hmelo et al, 2009; Lavi et al, 2020), dynamic thinking (Hrin et al, 2017; Maani & Maharaj, 2004), cyclic thinking (Ben‐Zvi‐Assaraf & Orion, 2005; Hrin et al, 2017), and interdisciplinary thinking (Stratford et al, 1998; You et al, 2018). Mambrey, Timm, et al (2020) offered a more operationalized definition: “as a conceptual skill in which superordinate principles of complex systems are taken into account when understanding and predicting the interplay and function of their elements” (p. 3).…”

Section: Conceptual Framework and Literature Reviewmentioning

confidence: 99%

Building a computational model of food webs: Impacts on middle school students' computational and systems thinking skills

Rachmatullah

Wiebe

2021

J Res Sci Teach

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Integral to fostering computational thinking (CT) skills, which are increasingly essential in today's digital era, has been the shift of paper‐based pictorial modeling activities to computational modeling. Research has indicated that modeling activities can advance students' understanding of a system's mechanism (i.e., systems thinking), such as an ecosystem. The current study examines the impacts of paper‐based pictorial and computational modeling activities on students' systems thinking and CT skills. A total of 751 seventh‐grade students were involved in online modeling activities, spanning over 4 days, and were assigned purposefully to a paper‐based modeling condition (n = 374) or a computational modeling (n = 377) condition. They took systems‐thinking‐embedded food web and CT assessments before and after the four activities, in addition to a formative assessment after each activity. Multilevel modeling and repeated‐measures correlation tests were used to analyze the students' quantitative data. Epistemic network analysis (ENA) was utilized to map out students' perceptions of what they believed they learned from the activities. The results revealed significant increases in the systems thinking‐embedded food web constructs in both conditions. However, the increase of CT skills in the paper‐based pictorial condition was not as significant as the increase in the computational modeling condition. ENA results showed that students in the computational modeling condition had more co‐occurrences between science and computer science or CT concepts than those in the paper‐based pictorial condition. These findings illuminate the benefit of engaging students in computationally rich science activities to advance both systems thinking and CT skills.

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Model-Based Systems Thinking: Assessing Engineering Student Teams

Cited by 23 publications

References 28 publications

Systems thinking assessments in engineering: A systematic literature review

Systems thinking assessments in engineering: A systematic literature review

Introducing the Privacy Aspect to Systems Thinking Assessment Method

Building a computational model of food webs: Impacts on middle school students' computational and systems thinking skills

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