Modeling the factors affecting the technology integration levels of secondary school teachers with data mining

The aim of this research is to examine in detail the order of importance of the factors affecting the technology integration levels of teachers working in public schools in Sanlıurfa in the 2021-2022 education period. The sample of the research, in which the decision tree method, one of the data mining methods, is used, consists of 1075 teachers working at the secondary school level of public schools in Sanliurfa in the 2021-2022 academic year. The variables explaining the technology integration levels of the teachers were determined through the applied demographic information form and the "Basic Indicators for Teachers' Technology Integration Scale". In the study, the analysis of the data was made with the "SPSS Statistics 25" package program, with the decision tree method, which is the most preferred data mining method. As a result of the research, it has been determined that the most important factor affecting the technology integration level of teachers is the factor of "Receiving/Not Taking In-Service Training". Afterwards, it has been determined that the "Branch" and "Administrators' Support/Not Offering" factors have equal and secondary importance. It has been determined that the third degree important factors are "Technological Infrastructure of the School", "Computer Usage Experience", "Teacher Service Period" and "Age" factors.