Analyzing Factors Influencing Vocational High School IT Program Students' University Choices Using Association Rule Mining

The complex masses of data that have emerged with increasing data generation and storage have increased the need for computers and software with more advanced computing capabilities to process this data. However, extracting meaningful information from complex data remains a challenge. Data mining, particularly in collaboration with artificial intelligence algorithms, works to uncover intricate relationships within data. One of the complex problems to be solved is guiding high school students toward university departments that will optimize their performance. This study investigates the factors influencing the university department preferences of vocational high school information technology students and graduates in the field of computer science. Unlike previous research, has typically focused on academic performance and current educational contexts, this study explores the connections among students' past educational experiences, preferences, habits, and hobbies, tracing these back to primary and secondary education. As a case study, the research centers on the computer engineering department, revealing that students who wish to study or are studying computer engineering show a greater interest in activities related to design and game development, have a preference for the C# programming language, and exhibit a particular interest in chemistry, while demonstrating less affinity for street games. These findings underscore the relationship between students' higher education preferences in computer science and their prior learning experiences and social preferences, offering deeper insights into the decision-making process.