Analysis of Student Study Pattern for Personalized Learning using an Innovative Approach - Rao, Aaryan; Goudar, R.H; G M, Dhananjaya; Rathod, Vijayalaxmi; Kulkarni, Anjanabhargavi (EAI Endorsed Transactions on Internet of Things, 2024)
In an era of rapid technological advancements, the area of Artificial Intelligence and Machine Learning (AIML) is revolutionizing the way we learn and interact with technology. However, this influx of information can be over- whelming for students, making it challenging to absorb and retain knowledge within a short timeframe. Learning preferences vary greatly from individual to individual, with some students preferring video tutorials, others favouring hands- on practical experiences, and still others relying on traditional textbooks. To ad- dress this diverse range of learning styles, i.e., a need for an interactive application that provides regular assessments following each lesson, regardless of the chosen learning method. This application would analyse each student's performance to identify their most effective learning approach. This personalized approach is particularly valuable in large coaching institutes, where a limited number of instructors cannot effectively monitor the progress of thousands of students simultaneously. By incorporating additional learning materials and implementing specific adjustments, this application can significantly enhance the learning experiences to students and adult learners alike, empowering them to navigate the complexities of technology with greater confidence and ease.
Keywords: Personalized learning; Machine learning; Education; Artificial Intelligence; study improvement application; student study analyser