Edugenius: AI-Powered Smart Learning for The Future

Abstract — In an age where learning opportunities are abundant but time and attention are limited, personalized learning has become more important than ever. This paper introduces EduGenius, an AI-powered web platform designed to help learners achieve their goals through customized learning experiences. Users can input a topic they want to learn, along with their available time, language preference, and current skill level. The system then generates a personalized roadmap, complete with curated resources, schedules, and quizzes. Using generative AI, EduGenius dynamically adjusts the roadmap based on feedback and quiz performance to keep the learner on track. Progress is visualized through intuitive dashboards, and a gamified interface keeps users engaged with rewards like badges and points. EduGenius combines the power of AI with human- centered design to make learning more effective, enjoyable, and tailored to each individual.

Personalized learning, Artificial intelligence (AI), Generative AI Progress tracking, Quiz generation

1. M. Murtaza, Y. Ahmed, J. A. Shamsi, F. Sherwani, and M. Usman, “AI-based personalized e-learning systems: Issues, challenges, and solutions,” IEEE Access, vol. 10, pp. 126399–126417, Dec. 2022. [Google Scholar] [Crossref]

2. Author(s) not specified, “Privacy preserved reinforcement learning model using generative AI for personalized e-learning,” IEEE Trans. Consum. Electron. In press. [Google Scholar] [Crossref]

3. W. S. Sayed, A. M. Noeman, A. Abdellatif, M. Abdelrazek, and M. G. Badawy, “AI-based adaptive personalized content presentation and exercises navigation for an effective and engaging e-learning platform,” Multimedia Tools Appl., vol. 82, pp. 19001–19025, Sep. 2023. [Google Scholar] [Crossref]

4. S. Amin, M. I. Uddin, W. K. Mashwani, and A. A. Alarood, “Developing a personalized e-learning and MOOC recommender system in IoT-enabled smart education,” IEEE Access, vol. 11, pp. 30566–30581, Apr. 2023. [Google Scholar] [Crossref]

5. R. Sajja, Y. Sermet, M. Cikmaz, D. Cwiertny, and I. Demir, “Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education,” arXiv preprint, arXiv: 2303.14080, Mar. 2023. [Google Scholar] [Crossref]

• Most Advanced Construction Material for Typical Boilers
• Nutrigenetic Impact of PEMT Gene Polymorphism Rs7946 On Choline Metabolism and Its Role in Personalised Nutrition
• Evaluating the Influence Factors of Media on Investor Sentiment Towards Stock Market Investments.
• To Compare the Effectiveness of Manual Traction and Mechanical Traction in Patient with Cervicogenic Headache
• Is Green Human Resource Management the Newest Trend or A Strategic Necessity?