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In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is described. The approach defines which concepts from domain knowledge should be included in the initial test so the system can make conclusions about whatdoi:10.3926/jotse.755 fatcat:2e4uyt4tkrfhdaay4fadz6krle