E-testing systems are being widely adopted in academic environments, as well as in combination with other assessment means, providing tutors with powerful tools to submit different types of tests in order to assess learners’ knowledge. In our process we present an approach and a system to let tutors monitor several important aspects related to online tests, such as learner behavior and test quality. The approach includes the logging of important data related to learner interaction with the system during the execution of online tests and exploits data visualization to highlight information useful to let tutors review and improve the whole assessment process. Main focus is discovering behavioral patterns of learners and conceptual relationships among test items. Experimental tests detect several correlations among questions, which gives useful feedbacks on the test quality.