Factors Affecting Predicting Teacher Evaluation in Higher Educational Institutions Among Faculty Members based on SA-BiLSTM

To keep up with good teaching standards and pedagogical improvements, it is vital to predict assessment of higher education teachers. Based on principles of pragmatism, psychology, and pedagogy, this research should contribute to the development of diagnostic procedures and training standards that may be used in many educational settings. Because of the three-tiered speciality training architecture used to prepare teachers in master's degree programs in education in Ukraine, institutions there require a differentiated approach. Model training, feature extraction, and preprocessing are all parts of the proposed methodology. While translating, cleaning, reducing, and normalising data is part of data preparation, feature selection uses correlation and mutual information criteria to establish the significance of variables. Following feature selection using information gain, the SA-BiLSTM model begins training. Different institutional features were associated with unique approaches to teacher preparation, according to a comparison of active empathy and the growth of pedagogical reflection. The SA-BiLSTM model outperforms SA and BiLSTM when it comes to predicting teacher ratings. The results show how important it is to have different levels of individualised strategies for preparing teachers. Institutions can improve training and instruction with the support of the predictive approach, which better evaluates teachers.