Neutrosophic Wavelet Time-Series for University Classroom Teaching Quality Analysis: A Multi-Resolution (T, I, F) Framework with Computations

This paper presents a method for analyzing teaching quality using a neutrosophic wavelet framework. Weekly scores from three courses are treated as time series and decomposed using the Haar wavelet transform. The mean of the series represents the underlying trend (truth), the distribution of detail energies across scales captures variability (indeterminacy), and the energy of negative details reflects performance shortfalls (falsity). These components form a neutrosophic triplet (T,I,F) for each course. The method is applied to normalized scores over eight instructional weeks. I&P Theory shows strong performance with low uncertainty and downside risk, while Calculus I and Data Structures display more variability or shortfalls. A scalar index, the Neutrosophic Wavelet Teaching Quality Index (NW-TQI), integrates the triplet for comparison. The approach is transparent and reproducible, offering more nuanced insight than simple averages or standard deviations. It can be extended with real classroom data, richer wavelets, and predictive models for educational diagnostics.