Smart Personalised Learning System

Shivdarshan Hasbe, Satish Gujar

Abstract: A Personalised Learning Platform leverages data analytics, machine learning and adaptive technology to tailor educational content to each student's particular strengths, interests, and rates of learning. The traditional classroom setting typically uses a single teaching method that all students are expected to follow, which often does not account for the varying degrees of understanding, prior knowledge, and engagement among individual learners. The approach taken here is to use an intelligent system that continually monitors how a student interacts with the Learning Management System (LMS), tracks his or her academic performance as a function of time (i.e., using timeseries analysis), and relies on data mining algorithms to identify behaviour patterns and recommend appropriate educational resources, quizzes, and feedback during the learner's interaction with the LMS. The overarching functions of this system are to create personalised learner profiles, deliver content that matches each profile (i.e., adaptive content delivery), assess the learner on a continuous basis, and monitor his or her overall progress in real time. The system will have numerous features that support learners in a collaborative manner and allow them to be part of a community of learners by sharing common interests and collaborating with others on the Learning Management System. By employing these recommendation algorithms and analysing students past performance, the proposed intelligent system will ultimately improve student participation, retention of information learned at school and higher academic achievement. The proposed research will also provide an overview of the intelligent system's architecture, major components/operations, and the measurement metrics utilised for effectiveness measurement. Based on initial experimental results, personalised learning has increased learner satisfaction and understanding vs. the historical model; thus, providing evidence as to how intelligent personalisation can change the way digital education is delivered and create a better, more efficient and learner-focused education model.

Keywords: Spam detection, email security, machine learning, deep learning, phishing, natural language processing, cybersecurity, transformer models