Control engineering education critical success factors modeling via Fuzzy Cognitive Maps

Yeşil, Engin; Ozturk, Cihan; Dodurka, M. Furkan; Şahin, Atakan

doi:10.1109/ithet.2013.6671061

Cited by 16 publications

(6 citation statements)

References 36 publications

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“…For example, in D20, the dynamicity of FCM affords dynamic adaptive instruction in an e-learning environment to provide personalized learning based on learners' needs and preferences [47]. Yesil et al [48] in study D14 conducted six simulations by adjusting the values of input concepts to determine their significance as success factors in control engineering education. They aimed to explore the optimal adoption strategy of blockchain technology to enhance the performance of the governmentsupported free basic education system in India.…”

Section: Reflectivementioning

confidence: 99%

The Application of Fuzzy Cognitive Mapping in Education: Trend and Potential

The,

Kudus

2024

TEM Journal

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Fuzzy cognitive mapping (FCM) is a valuable tool for understanding complex issues due to its ability to express complex and uncertain knowledge domains with dynamic modelling capabilities. This study focuses on the application of FCM in education, using a bibliometric analysis and systematic review of publications in the Scopus database from 2000 to October 2023. Using keywords related to FCM and education, the study retrieved fifty-four publications for frequency analysis and citation metrics. This study showcases its results by leveraging standard bibliometric indicators, encompassing metrics such as publication growth, top-cited publications, country contributions, and preferred publication titles. Findings from the systematic review reveal the potential of FCM in providing explanatory, predictive, reflective, and strategic insights and solutions to numerous educational issues.

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Section: Reflectivementioning

confidence: 99%

The Application of Fuzzy Cognitive Mapping in Education: Trend and Potential

The,

Kudus

2024

TEM Journal

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“…The literature on ABET shows that the studies that systematically present holistic and generic list of CSFs to acquire ABET accreditation are scant. There is a study [20] that has identified the list of CSFs in this context but focus is on control engineering program success rather than the process of ABET accreditation in general. The observation on the ABET accreditation process in multiple programs for the last five years have led to the identification of following 11 CSFs grouped into three categories.…”

Section: Critical Success Factors For Academic Quality Assurance and mentioning

confidence: 99%

Implementing Fuzzy AHP and FUCOM to evaluate critical success factors for sustained academic quality assurance and ABET accreditation

Ahmad¹,

Qahmash²

2020

PLoS ONE

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The Accreditation Board for Engineering and Technology (ABET) accredits the tertiary education programs in the areas of applied and natural science, computing, engineering, and engineering technology. ABET offers accreditation in the United States and other regions in the world that lack such entities such as Gulf Cooperative Counties (GCC). Though ABET accreditation is voluntary, graduates of the ABET-accredited programs are considered equivalent in knowledge, behaviors, and attitude with global standards. The process of ABET accreditation takes months or years depending upon the gap with readiness and resources. The objective of this study is to compile and prioritize the list of critical success factors (CSFs) to commit resources optimally for sustained academic quality assurance and ABET accreditation. The triangulation research designed has been employed. Firstly, the observation of the ABET accreditation process of multiple programs at King Khalid University (KKU) helped in identifying 11 CSFs in three categories namely Program design and execution, Quality culture and excellence, and Institutional infrastructure and support. Further, these CSFs have been explored in the literature in the area of ABET accreditation. Finally, the research employs a fuzzy analytical hierarchy process (Fuzzy AHP) and full consistency method (FUCOM) to rank the relative importance of these CSFs and their dimensions for sustained academic quality assurance and ABET accreditation. The incorporation of these CSFs will help institutions in the GCC and other regions to get their academic programs ABET-accredited in an optimal manner.

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“…One possible reason for the lack of reported investigation into goal-oriented FCM analysis is the difficulty in reversing the matrix multiplication and non-linear transformations involved in computing successive FCM states [4]. As mentioned in [5], there is a vast interest in FCMs and this interest on the part of researchers and industry is increasing, especially in the areas of control [4], [6], [7], business [8], [9], medicine [10]- [12], robotics [13], emotion modeling [14], environmental science [15], [16], education [17], information technology [16] and self-tuning controller design [19].…”

Section: Introductionmentioning

confidence: 99%

Triangular fuzzy number representation of relations in Fuzzy Cognitive Maps

Yeşil

Dodurka

Urbas

2014

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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In this paper, the conventional Fuzzy Cognitive Maps (FCMs), which has already achieved success in many fields, are extended by using triangular fuzzy numbers (TFNs). The advantage of FCMs is that they are relatively easy to construct and parameterize and are capable of handling the full range of system feedback structure, including density-dependent effects. However, it is a well-known fact that there are some limitations inherent in FCM, such as lack of adequate capability to handle uncertain information and lack of enough ability to aggregate the information from different sources. Triangular fuzzy numbers which are represented by a triplet has the capacity to represent the uncertain relations between the concepts. In this context, the weight matrix representing the causal relations are enhanced to a fuzzy weight matrix that has TFNs as element. As a result of this improvement, the dynamic reasoning algorithm of the conventional FCM is improved for the use of the proposed novel FCM. The proposed FCM is presented via four simulations and the results are discussed. The results of the simulation study shows how easily the uncertain information can be represented and interpreted by the proposed FCM design methodology.

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Control engineering education critical success factors modeling via Fuzzy Cognitive Maps

Cited by 16 publications

References 36 publications

The Application of Fuzzy Cognitive Mapping in Education: Trend and Potential

The Application of Fuzzy Cognitive Mapping in Education: Trend and Potential

Implementing Fuzzy AHP and FUCOM to evaluate critical success factors for sustained academic quality assurance and ABET accreditation

Triangular fuzzy number representation of relations in Fuzzy Cognitive Maps

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