learning styles, adaptivity, adaptive testing, self-testing, adaptive testing algorithm, motivation

In the school environment, terms such as personalization, individualism and adaptivity are becoming more and more frequent. The teacher is faced with a difficult task ? try to meet every student?s needs and requirements, their individuality and the way and pace in which they learn. The teacher does everything in their power to teach every student what they intend to teach them and what they expect them to know. What options does the teacher have? One of the options is to take different learning styles into account and work with the study material which suits the particular student?slearning style ? as far as the visual student is concerned, the teacher will need graphs, tables, diagrams or schematic notes; the kinaesthetic student, on the other hand, will require video recordings or practical applications. Another option is to adjust to individual students when evaluating their knowledge, i.e. during testing. How can the ?adjusting? be realized? Can it be achieved by adjusting to students? level of knowledge or rather by adjusting to their learning styles? And does this kind of adaptive testing have an impact on better understanding and preservation of knowledge? The paper deals with the issue of adaptive testing and tries to answer the above questions. Our research was aimed not only at the real testing (question ? answer), but also at the so-called self-testing. By self-testing we mean repetition of knowledge before the real testing, i.e. when the student goes through different variants of test questions and tries to answer them correctly. The student can answer each question multiple times. After each attempt, they can use ?Hints?, ?Study Material? or ?Help?, all of which should help them answer the question correctly. For both the self-testing and real testing, an algorithm has been created which takes the student?s current level of knowledge into account when selecting the next test question.