Enhancing Assessment of Students' Knowledge Using Fuzzy Logic in E-Learning

Assessing students' knowledge in the e-learning environment is a very complicated task. This is valid even more if the assessment is used as an input for further processing by an adaptive system that should generate personalised learning content. Assessment of students' knowledge, which is part of the proposed model of an adaptive e-learning system, lies in the focus of this paper. The model as a whole is created for significant optimisation of English language learning which is based on using Learning Management Systems (LMS). In comparison with traditional static models of e-courses, which actually offer a uniform content to all students, the proposed model offers its users/students adaptation in the area of their knowledge level and learning style (their combination respectively). In addition, the model is supported by automated decision-making processes, which are the most significant tool for optimising language learning. Automation of such decision-making processes is required in several areas. Knowledge assessment, which is one of the crucial ones, results in obtaining desired inputs for ideal progress in further steps of student's learning process. Such input information provided by the student carries a certain extent of uncertainty, thus it is necessary to base the decision-making processes on IF-THEN rules supported by a fuzzy-oriented expert system. The adaptive system for decision-making support will then enable automated creation of study variants suited to each individual student's needs, which current learning management systems do not enable.