Artificial Intelligence Techniques for Adaptive Personalized Learning Systems
Keywords:
Adaptive learning systems, Artificial Intelligence, Educational data mining, Learning analytics, Machine learning, Personalized learning, Study plannerAbstract
Artificial Intelligence (AI) is one of the solutions that has undergone a paradigm shift in the current education systems, providing smart solutions that enhance learning and academic efficiency. The conventional methods of study planning are based on fixed schedules, which are not responsive to personal learning capabilities, performance, and time constraints. Due to this, several students have difficulty managing their time, prioritizing their subjects poorly and using poor learning strategies. The study suggests the creation and deployment of a personalized learning planner, an AI-based study planner capable of dynamically creating adaptive study plans by analyzing student learning behavior and student performance analytics. The suggested system will combine machine learning, learning analytics, and recommendation algorithms to process student educational data and generate student-specific study plans. The system allows a dynamic and responsive learning process by constantly tracking the progress of students and reshaping their schedules. The proposed system has the following architecture: data collection, user profiling, machine learning analysis, and intelligent schedule generation modules. Empirical research indicates that Learning systems based on AI planning of studies can be used to enhance student productivity, efficiency in time management and academic achievements with significant effects. The study indicates that artificial intelligence could help revolutionize the educational planning system and facilitate personal learning processes. The further evolution of this field can incorporate new powerful deep learning solutions and real-time analytics to expand the possibilities of personalization.
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