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Vol. 8, Issue 1 (2019)

Comprehensive educational assistant application for enhanced learning support

Dr. Amit KR Tyagi
Choosing the right college and accessing relevant study materials are crucial for aspiring engineering students. This research paper introduces an Educational Assistant website that incorporates an intelligent prediction model to suggest colleges based on the student's Joint Entrance Examination (JEE) rank and branch preferences. Furthermore, the website offers personalized book recommendations tailored to the student's preferred branch of study. The Educational Assistant website uses machine learning algorithms and data analysis techniques to provide accurate and insightful college recommendations. By incorporating the student's JEE rank and branch preferences, the system dynamically matches their rank and category with suitable colleges, including prestigious institutions like Indian Institutes of Technology (IITs) and National Institutes of Technology (NITs). To enhance the educational experience, the website's recommendation system extends beyond college selection. By understanding the student's preferred branch of study, the system curates a customised list of book recommendations. The user interface of the website is designed to be intuitive and user-friendly. Students can effortlessly input their JEE rank and indicate their branch preferences, empowering them to receive personalized college suggestions and book recommendations instantaneously. The system's predictive capabilities and intelligent algorithms create a seamless and efficient experience for students navigating through their educational options.
Pages: 777-783  |  90 Views  37 Downloads

The Pharma Innovation Journal
How to cite this article:
Dr. Amit KR Tyagi. Comprehensive educational assistant application for enhanced learning support. Pharma Innovation 2019;8(1):777-783. DOI: 10.22271/tpi.2019.v8.i1m.25413

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