A personalized Learning system : education by AI

Abstract

Artificial intelligence application to personalized learning systems has become an evolutionary component in education opening many opportunities but also exposing some issues and ethical dilemmas. This study is focused on the period between 2010 and 2020, including the opportunities given by AI-based personalized learning systems such as AWS Elastic Beanstalk, to transform the regular learning models. The research provides several AI trends in education. At the forefront of our journey into AI-driven advancements stands the AWS Cloud, a dynamic platform renowned for its scalability, reliability, and unparalleled breadth of services. Within this expansive ecosystem, we have harnessed the capabilities of Elastic Beanstalk to deploy our backend application, serving as the cornerstone of our data processing endeavours. AI-enabled intelligent tutor systems and adaptive learning platforms which tend to likely improve student engagement, motivation, and academic achievement by offering individualized learning solutions tailored to student needs and preferences. In our AWS infrastructure, Elastic Beanstalk efficiently deploys our backend application, seamlessly integrating with ChatGPT API for robust data processing. Simultaneously, Relational Database Service (RDS) provides a secure SQL database solution for storing student data. With Elastic Beanstalk's scalability and RDS's reliability, we ensure our application processes data with precision while maintaining the integrity of critical student information. Ethical norms and policies applied in AI systems acquire attention due to risks like biased algorithms, breaches of data privacy, and accessibility issues. Suggestions include focusing on ethical issues, engaging stakeholders, performing longitudinal studies, and developing of innovation culture in the educational system.