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English Teaching Quality Evaluation Based on Analytic Hierarchy Process and Fuzzy Decision Tree Algorithm.

Huiyang Zhu1

  • 1School of Foreign Languages, Hubei University of Science and Technology, Xianning, Hubei 437199, China.

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This study introduces a novel fuzzy decision tree algorithm to evaluate English teaching quality in Chinese higher education. The developed system enhances evaluation accuracy and efficiency for administrators.

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Area of Science:

  • Educational Technology
  • Artificial Intelligence in Education
  • Higher Education Pedagogy

Background:

  • Globalization has increased English importance in China's economy and international trade.
  • Colleges and universities are raising English proficiency and teaching quality standards.
  • Assessing English teaching quality is complex and requires scientific evaluation systems.

Purpose of the Study:

  • To develop a scientific and sensible evaluation system for English teaching quality in colleges.
  • To investigate the quality of English instruction using advanced algorithms.
  • To provide data for university administrators to enhance teaching quality.

Main Methods:

  • Established an evaluation index system (EIS) using the Analytic Hierarchy Process (AHP).
  • Applied a fuzzy decision tree algorithm for teaching quality evaluation.
  • Tested the practical application and accuracy of the proposed algorithm.

Main Results:

  • The fuzzy decision tree algorithm demonstrated higher accuracy compared to other methods.
  • The system provides valuable teaching evaluation data for university administrators.
  • The proposed method improves the efficiency of evaluating English teaching quality.

Conclusions:

  • The developed AHP-based EIS and fuzzy decision tree algorithm offer an effective approach to assessing English teaching quality.
  • This methodology aids in enhancing the overall quality of English education in higher institutions.
  • The findings support data-driven decision-making for improving pedagogical practices.