Personalized Education Platform
Keywords:
Adaptive assessment, AI in education, Digital certification, E-learning, Personalized learning, Recommender systemsAbstract
The global e-learning industry has transformed rapidly due to digital technologies, internet expansion, and evolving pedagogical approaches, with the market projected to exceed USD 400 billion by 2028. Despite growth, existing Learning Management Systems (LMS) and Massive Open Online Courses (MOOCs) face high dropout rates, limited personalization, and inconsistent certification. This paper presents a Personalized Education Platform that addresses these issues using AI-driven personalization, intuitive interfaces, and verifiable certifications. Leveraging large language models (LLMs), recommender systems, and adaptive assessments, the platform constructs individualized learning pathways. A diagnostic quiz profiles learners’ strengths and goals, guiding an AI recommendation engine to suggest appropriate courses. A dynamic dashboard tracks progress, and metadata-enriched certificates enhance credibility. The proposed platform is designed to improve engagement and reduce dropout tendencies, as suggested by existing literature and preliminary prototype validation. This platform advances learner-centred, adaptive, and certification-integrated digital education, aligning with global trends and paving the way for next-generation Learning Experience Platforms (LXPs).
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