Entropy Value-Based Pursuit Projection Cluster for the Teaching Quality Evaluation with Interval Number

Area of Science:

• Educational Measurement
• Data Analysis
• Quality Management

Background:

• Quantifying student academic performance and learning achievement is crucial for assessing teaching quality.
• Existing methods often struggle with the uncertainty inherent in interval number data.
• A robust model is needed to identify, evaluate, and monitor key factors influencing teaching quality.

Purpose of the Study:

• To develop a novel model for evaluating teaching quality using interval number data.
• To objectively determine the weights of various indicators influencing teaching quality.
• To enhance the identification, evaluation, and monitoring of teaching quality factors.

Main Methods:

• A projection pursuit cluster evaluation model was proposed.
• The entropy value method was employed for model weight determination.
• Monte Carlo simulation transformed interval numbers into real numbers for simplified analysis.

Main Results:

• The proposed model successfully simplified the evaluation of interval number indicators.
• Objective weights for each index were obtained, reflecting their importance.
• The model provided a clear evaluation of teaching quality based on collected data.

Conclusions:

• The developed model offers an effective approach for assessing teaching quality under interval number conditions.
• This method provides objective insights into educational processes, aiding performance improvement.
• The study contributes to a better understanding of factors influencing teaching effectiveness in higher education.