تحفيز الطلاب الجامعيين على المشاركة في التعلم الإلكتروني المتزامن باستخدام بيانات المنطق الضبابي

Motivating Undergraduate Participation in Synchronous e-Learning Using Fuzzy Logic Data Driven

The Covid-19 pandemic has disrupted the traditional education system, leading to a significant shift towards online education. However, this transition has brought forth challenges in terms of communication and engagement between instructors and students. Many instructors and students have expressed concerns about poor communication and disengagement during online classes. To address these issues, we propose a solution to enhance the interaction between lecturers and students, ultimately improving student engagement.

Our proposed solution utilizes various parameters during synchronous learning to provide lecturers with valuable insights. By analyzing students’ interactions and feedback in real-time, lecturers can address questions and highlight specific topics based on student engagement. Additionally, the solution incorporates fuzzy logic principles to track and monitor students’ activities during online classes, generating live statistical data.

The primary objective is to enhance students’ simultaneous participation in online lessons. By tracking and analyzing students’ events and providing statistical evaluations to lecturers by using fuzzy logic principles, the proposed solution aims to increase student participation and improve the overall learning experience in online classes. This data-driven approach aims to create a more interactive and engaging online learning environment.

By leveraging the power of data analysis and fuzzy logic principles, our solution aims to bridge the communication gap between lecturers and students in the online learning space. This will ultimately lead to improved student engagement and better learning outcomes in the e-learning ecosystem.