Abstract
This research analyses the non-academic factors in order to predict the qualifying test results of applicants to the software engineering training program. Huge interest to the IT industry in Ukraine requires highly adaptive learning methods in education. Discovering factors that influence academic performance may led to a quicker response to an industry needs. It is reflected on on-the-fly adaptation of curriculums and more personalized learning methods. During the research we reviewed the data mining methods in order to classify the candidates’ data based on qualifying test results. The qualifying test is aimed to discover the initial level of knowledge of candidates and is the main criteria for suitable selecting candidates to the training program. Discovered the main factor which has the most influence on initial knowledge level of candidates. Generated decision tree in order to analyze the most influenced factors.
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