Enhanced user-centred quality assurance framework for cooperative online learning

Abstract

The rapid expansion of online learning has highlighted the need for robust quality assurance frameworks prioritizing user experience and pedagogical effectiveness. While many existing frameworks focus on technical functionalities, they often neglect essential user-cantered aspects such as engagement, interactivity, and accessibility. This study proposes an Enhanced User-Cantered Quality Assurance Framework for Cooperative Online Learning in Jordanian universities, addressing the critical need for a structured approach that integrates instructor and learner perspectives. Using a mixed methods research design, the study incorporates qualitative and quantitative methodologies, including focus group discussions, individual interviews, and surveys. The research follows a three-phase process: needs assessment, participatory design, and evaluation. The participatory design approach ensures that both instructors and learners contribute to shaping the framework, fostering engagement and practical implementation. The study also examines the role of Artificial Intelligence (AI) in enhancing online learning by evaluating its impact on system quality, information quality, and service quality. The findings reveal that AI-driven features significantly improve user satisfaction and learning outcomes, yet challenges remain regarding usability, accessibility, and instructor readiness. The study’s results confirm that a user-centred quality assurance framework can bridge existing gaps in online learning by aligning technological advancements with the specific needs of users. The framework includes real-time analytics, continuous feedback loops, and adaptive learning tools to enhance engagement and effectiveness. The research contributes to the growing field of digital education by demonstrating the transformative potential of participatory design in developing quality assurance mechanisms that are both scalable and adaptable to evolving educational landscapes. This study presents a structured approach to improving cooperative online learning in Jordanian universities by addressing the deficiencies in current online learning platforms. The proposed framework enhances student engagement and instructional effectiveness and sets a foundation for future research in AI-driven quality assurance strategies. The findings underscore the necessity of integrating user-driven insights into digital education policies to ensure sustainable and inclusive online learning environments.