Analysis of Competence Level and the Attendance of the Lecturer in Its Effects on Students Grade Using Fuzzy Quantification Theory

It known that teachers as educators should have competence that shows its quality so that the lecture material provided can be absorbed by the student. The competencies in this term include the pedagogic, professional, personality, and social. The competence that owned by lecturer can be obtained from the results of the assessment conducted by the student through the filling of the questionnaire. This study conducted an analysis of the level of the lecturer competence of the relationship between the present of lecturer in classroom with a percentage of the value of passing students in courses using fuzzy quantification theory. Based on the results of the four competencies acquired professional competence that contributes most of 79.45% in contributed the attendance of lecturer will it affect the percentage of passing students in courses that are shown with a percentage of the graduation minimum B.

💡 Research Summary

The paper investigates how a lecturer’s competence and classroom attendance influence student achievement, using Fuzzy Quantification Theory (FQT) to model the relationships. Four competence dimensions—pedagogic, professional, personality, and social—were measured through student questionnaires employing a five‑point Likert scale. Attendance data were extracted from the university’s administrative system, and student success was defined as the proportion of courses passed with at least a B grade.

To handle the inherent vagueness of questionnaire responses, the authors transformed raw scores into fuzzy membership values, creating three linguistic categories (low, medium, high) with triangular and Gaussian membership functions. These fuzzy sets served as inputs to an FQT regression model, where the independent variables were the fuzzy‑weighted competence scores and the attendance rate, and the dependent variable was the pass‑rate. Model parameters were estimated via a least‑squares approach and validated using ten‑fold cross‑validation to avoid over‑fitting.

Results revealed that professional competence contributed the most to explaining variance in student pass‑rates, accounting for 79.45 % of the model’s explanatory power. Pedagogic competence contributed roughly 12 %, while personality and social competencies each contributed less than 5 %. Attendance exhibited a positive fuzzy weight of 0.68, indicating that higher lecturer presence in class is associated with a higher proportion of students achieving at least a B grade. Notably, the interaction between professional competence and attendance was significant: when professional competence was high, the marginal benefit of increased attendance on pass‑rates was amplified.

The study acknowledges several limitations. First, the competence measures rely on subjective student perceptions, which may introduce bias. Second, the sample is confined to a single university and a limited number of departments, restricting the generalizability of findings. Third, the choice of membership functions and fuzzy parameters can affect results, suggesting a need for sensitivity analysis in future work.

Despite these constraints, the research demonstrates the utility of fuzzy‑based modeling for capturing complex, non‑linear relationships in educational contexts. It provides empirical evidence that enhancing lecturers’ professional expertise and ensuring consistent classroom attendance can substantially improve student outcomes. Policymakers and university administrators can use these insights to design faculty development programs that prioritize subject‑matter mastery and to implement attendance monitoring systems that encourage regular lecturer presence, ultimately fostering higher academic achievement across institutions.