This research focused on developing a new smart framework to be applied to online learning. This smart framework aimed to enable users to obtain online learning materials that fit with the user's abilities. User capabilities were classified using artificial intelligence (AI). This user ability classification aimed to get material that matched the user's ability. The AI algorithm used in this framework was K-Nearest Neighbor (K-NN). K-NN had the duty to process the pre-test result data and the results were matched with various attribute data owned by the user. In this study, a user ability classification test and overall system accuracy testing were based on the post-test results obtained after the user completed the learning he had done. The overall results of system testing obtained in this framework shown an average accuracy rate of 90% with an error of 10%.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL