A distance learning and assessment model in mathematics education based on fuzzy logic

Distance education is an education model in which the educator and the student come together independently of time and place and the learning process is continued. Although it has positive aspects in terms of time and space, it has limitations such as weak interaction and poor functioning of evaluation processes. In this thesis, the existing distance education models were examined, the deficiencies in distance education were determined, and a distance education model based on mathematics was proposed in order to eliminate these disadvantages. The proposed model uses machine learning approaches and fuzzy inference systems based on the student's mood, learning style, readiness level and concept maps for the contents. Since the created model modules are designed, the modules can also be used independently of each other. The examples and tests carried out on the proposed model showed that the model works student-centered, considers the cognitive status of the student, and provides objective evaluation.