Content analysis on the examination of artificial intelligence-supported applications in the assessment and evaluation stage in education

This study was conducted to examine AI-supported tools used in the field of measurement and evaluation. The research was carried out using a literature review method, and data were collected from 16 AI-supported measurement and evaluation tools used in the field of education. The obtained data were analyzed using descriptive and content analysis methods. The results show that AI-supported tools are primarily designed for universities and adults. When the usage areas of AI-supported tools were examined, it was found that they cover a wide range, from exam management and security to language education and writing-grammar analysis. The reviews revealed that mathematics and science dominate, but fields such as language and speech also hold significant importance. The tools are most commonly used in formative (process-oriented) and summative (result-oriented) evaluation types. AI-supported tools can mostly perform measurement and evaluation aimed at the cognitive domain. Most evaluations are conducted in the analysis stage of Bloom's Taxonomy, but students are mostly evaluated at the comprehension stage. It was determined that AI-supported tools used in the field of measurement and evaluation do not target students at the analysis stage of Bloom's Taxonomy. Significant findings were obtained regarding how these tools can be used more effectively in educational processes. With the development of educational technologies, the use of AI-supported tools will become more widespread and applicable in different fields. In this context, it was concluded that future studies should aim to increase the effectiveness and efficiency of AI-supported tools. Educators need to have more knowledge and skills in using these tools more effectively. Therefore, it is essential to develop training programs for teachers.