The paper summarizes the experience obtained during more than a decade of research on intelligent tutoring systems (ITSs) and, in particular, on their integral part – the knowledge assessment systems. Special attention is paid to challenges and issues of automation of knowledge assessment. Possibilities of automation, a teacher's workload, objectivity of comparison with standard, and the assessed knowledge level in accordance with Bloom's taxonomy are chosen for selection of appropriate format for students' submitted answers and/or solutions. The focus of the paper is on motivation to use concept maps (CMs) as knowledge assessment tool. Advantages of CMs are discussed and the basic conceptions for the developed adaptive intelligent knowledge assessment system IKAS are presented. The short overview of IKAS highlights the novel theoretical solutions that are implemented in the system. Lessons learnt from the practical usage of IKAS in seventeen different study courses are used to define the unsolved challenging problems and open questions for future work.