Assessing student learning outcomes using mixed diagnostic tests and cognitive graphic tools

Abstract

In this paper, we provide an approach to assessing student learning outcomes by using mixed diagnostic tests. These tests represent an optimal compromise between unconditional and conditional components and facilitate the development of individual learning paths, which, in turn, would provide students with the opportunity for self-guided learning. To construct individual learning paths, we apply an intelligent learning and testing system. Thus, each student becomes able to predict their learning outcomes following the respective learning path designed. In addition, we describe a cognitive graphic tool the 2-simplex prism to cognitively visualize the results of student learning assessment. We assume that our approach can be used when assessing student learning outcomes within any subject and propose applying this approach as a tool to enhance both student and teacher activity.