Superb Fairy-Wren Optimized Lightweight Convolutional Refinement Network for Analyzing Generational Teaching Differences and Efficacy In Malappuram, Kerala

Abstract

This study investigated the influence of generational teaching differences on educational efficacy within the Malappuram District, Kerala. Recognizing the limitations of existing deep learning models in analyzing these nuanced variations within a specific regional context, a Superb Fairy-wren Optimized Lightweight Convolutional Refinement Network (SFOA-optimized LCRN) was developed. This network captured complex and non-linear relationships within educational data to provide a robust framework for predicting teaching effectiveness. Optimization via the SFOA ensured efficient parameter tuning and enhanced model interpretability. Here, the data encompassing teacher demographics, survey responses detailing teaching methodologies, and quantitative measures of performance underwent rigorous preprocessing. This process included Multivariate Imputation by Chained Equations (MICE) for missing value imputation, Tanh-Estimator for outlier management, categorical data encoding through ordinal and one-hot encoding, textual data processing utilizing Natural Language Processing (tokenization, stemming, stop word removal), and numerical data normalization. The preprocessed data was analyzed through the SFOA-optimized LCRN to enable the identification of generational patterns along with the prediction of teaching effectiveness. The SFOA-optimized LCRN demonstrated significant performance improvements over existing models. Specifically, accuracy reached 99.7%, precision 98.95%, recall 98.87%, F1-score 98.91%, and specificity 99.02%. Furthermore, the model achieved an execution time of 91ms to highlight its computational efficiency. Practical recommendations, including tailored training programs, mentorship initiatives, and collaborative teaching strategies, were generated to address identified generational variations. These strategies aimed to foster an inclusive and technologically adaptive learning environment. The SFOA-optimized LCRN effectively analyzed generational teaching differences to lead to improved educational strategy development within the specified regional context.