Investigation of adults' participation in lifelong learning by using data mining techniques

Learning is evolving into lifelong learning by going beyond formal environments. Adult education, which is among the study subjects of lifelong learning, was studied in this study. Using the data set of the "Adult Education Research" survey published by the Turkish Statistical Institute (TUIK) in 2007, 2012, and 2016, it was aimed to determine the factors affecting the participation of adults in lifelong learning by data mining method. Micro data set was obtained with the permission of TUIK. The analysis of the data was carried out with the R package program. Results were obtained by applying C.05, CART, and CTREE algorithms from the decision tree method, mainly used in classification problems and provides forward-looking predictions, to the metadata set. According to the results obtained, it has been concluded that adults leave education unfinished due to unsuitable participation conditions and familial factors. Moreover, estimates such as "if the participant is unmarried and the need to participate in education is "yes," approximately 60% likely to relinquish due to unsuitable participation conditions" or "if the participant is married and a vocational or technical high school graduate, 70% likely to relinquish due to family factors" were revealed as the result of the analysis.