AIRAAIRA

Journal of Information Systems and Technology ResearchJournal of Information Systems and Technology Research

A novel educational system has been developed using the Radial Basis Function (RBF) algorithm to address the limitations of traditional classroom environments, which often rely on standardized material and fixed teaching methods. This research assesses recent advancements in interactive intelligent education systems by combining Artificial Intelligence (AI) with interactive teaching methods. A model based on cognitive functions is constructed using the RBF algorithm to personalize instructional approaches and foster a self-directed learning platform. The research methodology involves a comprehensive literature review, developing an Education Intelligent System (EIS) using AI-driven cognitive modelling, and the implementation of the RBF algorithm within a neural network architecture. The systems effectiveness is evaluated through empirical methods, including extensive data analysis and continuous refinement based on student performance feedback. Additionally, a network topology model is designed to enhance the systems adaptability for different roles within the educational framework. The results show significant improvements in instructional effectiveness, learner engagement, and personalized learning experiences. This research demonstrates that AI and interactive technologies can revolutionize conventional educational methods, enhance learner proficiency, and cultivate a more dynamic and engaging learning environment. Future work aims to improve the systems user interface and analyze larger datasets to refine the AI algorithms further.

This study demonstrates the effectiveness of an interactive online education system in enhancing the learning experience and improving the quality of educational materials.The research highlights the successful integration of the Radial Basis Function (RBF) algorithm to create a personalized and adaptive learning environment.Future research should focus on improving the systems user interface and refining the AI algorithms with larger datasets to further enhance its reliability and accuracy.

Future research should explore the potential of integrating augmented reality (AR) and virtual reality (VR) technologies into the intelligent education system to create more immersive and engaging learning experiences. Furthermore, investigating the long-term impact of personalized learning pathways on student motivation and academic achievement is crucial. Finally, a study could focus on developing robust ethical guidelines and data privacy protocols for AI-driven educational systems, ensuring responsible and equitable implementation of these technologies to address concerns about data security and algorithmic bias, ultimately fostering trust and acceptance among students, educators, and policymakers. These investigations will contribute to a more comprehensive understanding of how AI can be leveraged to transform education and empower learners in the digital age.

  1. Impact of Artificial Intelligence on Dental Education: A Review and Guide for Curriculum Update. impact... doi.org/10.3390/educsci13020150Impact of Artificial Intelligence on Dental Education A Review and Guide for Curriculum Update impact doi 10 3390 educsci13020150
  2. Artificial Intelligence in Education (Aied) a High-Level Academic and Industry Note 2021 by Muhammad... papers.ssrn.com/sol3/papers.cfm?abstract_id=3833583Artificial Intelligence in Education Aied a High Level Academic and Industry Note 2021 by Muhammad papers ssrn sol3 papers cfm abstract id 3833583
  3. The Ethics of Artificial Intelligence in Education | Practices, Challe. ethics artificial intelligence... taylorfrancis.com/books/9780429329067The Ethics of Artificial Intelligence in Education Practices Challe ethics artificial intelligence taylorfrancis books 9780429329067
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