Systems thinking assessments in engineering: A systematic literature review

Dugan, Kelley E.; Mosyjowski, Erika A.; Daly, Shanna R.; Lattuca, Lisa R.

doi:10.1002/sres.2808

Cited by 23 publications

(20 citation statements)

References 75 publications

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“…Further, data support the notion that once key habits of thinking are mastered, regardless of the context, learners tend toward more sophisticated thinking when new contexts are encountered (Mambrey et al, 2020). When it comes to assessment of this type of thinking, there is a gap in terms of how we measure both technical and contextual aspects of systems thinking (Dugan et al, 2022).…”

Section: Defining Systems Thinkingsupporting

confidence: 52%

Systems thinking tools to address SDG #4

Jordan

Gray

Sorensen

2023

Front. Sustain. Cities

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Section: Defining Systems Thinkingsupporting

confidence: 52%

Systems thinking tools to address SDG #4

Jordan

Gray

Sorensen

2023

Front. Sustain. Cities

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“…Whilst there are clear examples of studies exploring ST with cognitive neuroscience tools (i.e., through concept mapping and the use of fNIRS) in a laboratory setting (e.g., Hu et al, 2019 ) to our knowledge there is no research to date exploring the relationship between ST and observational learning and/or the use of CSA practices involving mobile neuroscience tools/measures in an LIC. A recent systematic literature review on systems thinking in engineering found that the triangulation of ST via multiple assessment types such as the use of concept mapping and fNIRS (Hu and Shealy, 2018 ) is likely to be beneficial (Dugan et al, 2022 ). To this end, we have proposed using NIRS and concept mapping similar to the approach taken by Hu and Shealy ( 2018 ) and the use of FCM which therefore provides several forms of triangulation ( Figure 2 ).…”

Section: Proposed Theory Of Change (Toc) and Limitationsmentioning

confidence: 99%

Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture

Lalani

Gray

Mitra-Ganguli³

2023

Front. Integr. Neurosci.

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Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space.

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“…Dugan et al (2022) conducted a systematic review of ST assessment in the field of engineering. This study investigated the ongoing ST assessment in engineering by a systematic review of existing assessments.…”

Section: Literature Review and Backgroundmentioning

confidence: 99%

The organizational systems thinking excellence model (OSTEM)

et al. 2023

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Today, the challenges facing organizations are more complex. The excellence level of systems thinking (ST) in an organization indicates the organization's ability to overcome these issues. This study aims to present an excellence model for assessing the level of ST in organizations. First, according to the systematic review process of documents related to ST and assessing ST, 39 documents have been verified in terms of quality and, by using the Critical Appraisal Skills Programme (CASP), the final documents were selected. Then, by three-stage coding of selected documents, codes, concepts and categories were identified. Based on the outputs of coding stage and placing the 2020 model of EFQM, the dimensions, criteria and sub-criteria for evaluation of ST in the organization were defined and organizational systems thinking excellence model (OSTEM) was developed. To evaluate the validity of the designed model, the content validity index (CVI) was used. The final model includes three sections: direction, execution and results.

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Systems thinking assessments in engineering: A systematic literature review

Cited by 23 publications

References 75 publications

Systems thinking tools to address SDG #4

Systems thinking tools to address SDG #4

Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture

The organizational systems thinking excellence model (OSTEM)

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