Implementation of Machine Learning and Fuzzy-Logic Rules for Intelligent Tutoring System Design on Photography

This research uses the concept of Intelligent Tutoring Systems (ITS) in field of photography to support the development of skills and knowledge of camera users with aim of becoming professional photographers. In order to predict skill and knowledge level of users, a system has been developed. The system involves machine learning and has been trained using data obtained from an open-source photography platform and processed to create an aesthetically valuable set of photos. The aesthetic value prediction system allows for an assessment of beauty of a photo image taken by a camera user. The assessment is given in the form of a score, which is defined as the ‘Aesthetic Score’. To determine a user's ‘Performance Level’, at least two inputs are required: ‘Aesthetic Score’ and ‘Test Score’. These inputs are then processed using Fuzzy-Logic rules to reach a conclusion. The experimental results indicate that our proposed system could predict skill and knowledge level of camera users. This aims to build a student model that becomes one of the key topics in the overall ITS design.