An analytical approach for an AI-based teacher performance evaluation system in Saudi Arabia's schools

Teacher performance evaluation is essential to a teacher's primary responsibilities. This study investigates the process of evaluating teachers' performance to provide a basis for planning an ongoing professional development program. AI-based systems present an opportunity for objective and reliable evaluations, facilitating the identification of areas requiring improvement and contributing to the overall enhancement of educational quality. Consequently, incorporating AI into evaluating teachers has become a research hotspot. This research proposes an analytical comprehensive AI-based system for teacher evaluation. Moreover, we introduce a novel analytical index system derived from the current adopted Key Performance Indicators (KPI) in the Ministry of Education in Saudi Arabia and an overall algorithm. This study is part of an integrated project to evaluate teachers' performance using AI. To build our model, we are accurately determining the evaluative weights through 13 workshops held with 283 field experts. The main hypothesis is that the weights were evenly distributed. After studying them, we found they were relatively different by 0.1 to 0.3%. By analyzing T-KPI, we believe that our proposed index system could overcome the limitations of human-based assessments as it assigned appropriate AI techniques for each, thus ensuring accurate, reliable, and objective evaluation. This innovation would also economically impact rationalizing spending and reducing costs. An AI-based teacher evaluation can overcome the subjective, time-consuming, costly, and inefficient limitations.T-KPI's analysis index defines the evaluation elements and potential AI technology.Assigning the actual weight for each element ensures the evaluation's accuracy.