KNOWLEDGE ASSESSMENT THROUGH THE APPLICATION OF COMPUTER ADAPTIVE TESTING IN RESPONSE TO MODERN TENDENCIES IN EDUCATION

Abstract

Education, at all levels, has undergone certain changes due to the Covid-19 pandemic. In the time of the pandemic, classes were held exclusively through online platforms or with a possible combination of traditional, frontal classes. Some institutions also conducted partial knowledge tests through online platforms with the possible inclusion of a video call meeting. The changes adopted at that time have largely remained even after the end of the pandemic. Online tests for self-assessment and assessment of knowledge are mainly based on a random question and answer generator. Such tests are not adapted to the current knowledge of the respondents themselves and thus negatively affect their motivation. Computer adaptive testing enables the test, ie the generated questions to be asked depending on the respondent's answer to the previously asked question (simulation of oral examination). This way of assessing knowledge has two positive effects, it gives the impression that the test has been created "just for him", while on the other hand it increases the effectiveness of testing because it reduces the number of questions to be answered to objectively assess the knowledge. This paper will describe the concept of an original, authorial CAT test model. The results of tests in the higher and secondary education system conducted using the above CAT model will also be presented.