Towards a more robust teaching evaluation by articulating M-estimators, the Friedman test, additivity tests, and reliability metrics
DOI:
https://doi.org/10.56219/dialgica.v23i2.6344Keywords:
statistical inference, statistical analysis, teacher assessmentAbstract
This research proposes a comprehensive statistical approach to evaluate teaching performance through robust estimators, normality tests, reliability analysis (Cronbach's alpha), Hotelling's contrast and Friedman's test. Using a quantitative methodology with a Likert scale applied to 160 students, the study aims to validate the instrument and identify strengths and areas for improvement. The results show adequate internal consistency and the absence of significant outliers, highlighting organization and feedback as strengths, while the applicability of learning and participative dynamism is identified as weaknesses. The multimethod approach proves to be a robust model, demonstrating that the integration of complementary statistical perspectives offers more solid and nuanced conclusions than any isolated technique.
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