Advance in online education recommender systems during and after Covid-19 a survey

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Abstract The Covid-19 pandemic has significantly accelerated the adoption of online education, necessitating the development and enhancement of recommender systems tailored to this context. This survey paper investigates the key advancements, impacts, challenges, adaptations, and ethical considerations associated with online education recommender systems during and after the Covid-19 pandemic. We explore the key factors considered in designing and implementing these systems, including user preferences, course content, pedagogical approaches, and scalability. Furthermore, we analyze how these recommender systems impact student engagement and learning outcomes by providing personalized learning experiences, access to diverse resources, and targeted skill development. The survey also sheds light on the challenges and limitations faced by these systems, such as limited In-Person Interaction, increased Demand for Online Education, and lack of Social Learning Opportunities. Moreover, we examine how online education recommender systems adapt to changing student needs and preferences in the dynamic post-pandemic landscape. Lastly, we address the ethical considerations and privacy concerns related to the use of these systems, emphasizing theimportance of transparency, data privacy, and addressing biases. This comprehensive survey serves as avaluable resource for researchers, educators, and practitioners interested in understanding and advancingonline education recommender systems during and after the Covid-19 pandemic.

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