Optimizing the Usage of Educational Tools for Effective Online Learning: A Proposed Optimization Model for Physics and Other Basic Science Courses

Online education has become increasingly popular in academic and scientific communities, and the COVID-19 pandemic has accelerated its adoption worldwide, particularly in developing countries. However, many instructors were unable to effectively utilize the available learning management system (LMS) educational tools due to their lack of experience, leading to less effective online education compared to traditional face-to-face teaching. To address these challenges, we propose an effective model for optimizing the usage of LMS educational tools by instructors. The proposed model is developed using Fuzzy logic and the Genetic optimization algorithm, and a flowchart is designed to facilitate its implementation. The model is applied to an undergraduate Physics course, and the output results are analyzed using statistical methods. Our findings demonstrate the positive impact of the proposed model on students' performance. The outcomes of this study can aid in the optimal design of online-course plans based on the utilized LMS educational tools while simultaneously improving students' learning. The proposed model has the potential to be adapted for use in various theoretical and, with slight modifications, for practical courses across different disciplines, contributing to enhancing the effectiveness of online education in the post-pandemic era.