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Research on evaluation model for virtual experiment teaching based on interval-valued fuzzy sets.

Qi Cao1, Wei Zhong1

  • 1Army Logistics University, Chongqing, China.

Evaluation and Program Planning
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Summary

This study introduces a new interval-valued fuzzy comprehensive evaluation (IVFCE) model for virtual experiment teaching (VET). The IVFCE model offers a more convincing and detailed assessment of VET quality, aiding continuous improvement.

Keywords:
Evaluation modelInterval-valued fuzzy comprehensive evaluationTeaching evaluationVirtual experiment teaching

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Area of Science:

  • Educational Technology
  • Fuzzy Mathematics
  • Data Analysis

Background:

  • Virtual experiment teaching (VET) evaluation is complex, involving multiple indicators and inherent uncertainties.
  • Traditional fuzzy evaluation methods can lose information when dealing with interval values.
  • Accurate VET assessment is crucial for pedagogical quality enhancement.

Purpose of the Study:

  • To propose an interval-valued fuzzy comprehensive evaluation (IVFCE) model for VET.
  • To address the challenges of uncertainty and information loss in VET evaluation.
  • To provide a more robust and informative evaluation framework for virtual experiments.

Main Methods:

  • Utilizing interval-valued fuzzy set (IVFS) theory to handle interval data.
  • Developing a multi-level comprehensive evaluation model for VET.
  • Comparing IVFCE results with traditional fuzzy comprehensive evaluation methods.

Main Results:

  • The proposed IVFCE model provides more convincing evaluation results.
  • The model effectively reduces information loss compared to traditional methods.
  • IVFCE facilitates a better understanding of VET criteria and areas for improvement.

Conclusions:

  • The IVFCE model enhances the accuracy and comprehensiveness of VET evaluation.
  • This approach better reflects the complexity and diversity of virtual experiment pedagogy.
  • The model supports continuous quality improvement in virtual experiment teaching.