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. 2021 Sep 14:12:593068.
doi: 10.3389/fpsyg.2021.593068. eCollection 2021.

Applying Fuzzy Fault Tree Method to Evaluate the Reliability of College Classroom Teaching

Liangliang Wang  1   2 , Mingfang Fan  1 , Feng Zhang  3
Affiliations

Applying Fuzzy Fault Tree Method to Evaluate the Reliability of College Classroom Teaching

Liangliang Wang et al. Front Psychol. .

Abstract

The evaluation of classroom teaching quality is closely related to the development of higher education as a scientific and effective evaluation system that can provide a solid foundation for formulating educational policies. Therefore, an evaluation model of classroom teaching quality in colleges and universities is established based on the fuzzy fault tree theory with "classroom teaching failure" as the top event to effectively evaluate the reliability of college classroom teaching and optimize the teaching strategies. In consideration of the lack of availability and dynamics of classroom teaching data, fuzzy numbers are used to describe the probability of underlying events. In addition, the top event probability of the fuzzy fault tree is calculated by the double-layer Monte Carlo method (MCM), which analyzes the classroom teaching effect based on the fuzzy fault tree reasonable. In summary, the quantitative evaluation system of classroom teaching quality based on fuzzy fault trees can evaluate classroom teaching more comprehensively and dynamically and help to improve the teaching quality of higher education.

Keywords: classroom teaching failure; college classroom; double-layer Monte Carlo; fuzzy fault tree; teaching evaluation.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Fault tree of classroom teaching effect.
Figure 2
Figure 2
Change law of failure probability with number change of outer layer sampling.
Figure 3
Figure 3
Change law of failure probability with number change of inner layer sampling.
See this image and copyright information in PMC

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