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Among the various kinds of learning analytics emerging especially in the latest decade, clicking patterns cover a prominent role, fostered by their success in analyzing several types of data concerning activity on the web. They can be defined as sets of clicks performed by users, in which every set is treated as the basic unit. Few research has been performed on clicking patterns in educational contexts. In this paper, we perform analysis regarding clicks to an online course in Mathematics, aimed at allowing students to follow courses at a distance, both before and after enrolling at University. We used clustering techniques on students learning behavior, which have been defined for this research as visualizations of activities and resources of the course, to detect differences on students' grade according to their online learning behavior. Our results show that students tend to proceed on the course in both activities and resources. There is no correlation between participation and course grades, even if the most active students show higher scores. Moreover, patterns differ significantly according to the degree program of each student, showing the importance of tailored path. [ABSTRACT FROM AUTHOR]

The study presented in this paper sought to explore several dimensions to online learning. Identifying the dimensions to online learning entails important basic issues which are of great relevance to educators today. The primary question is "what are the factors that contribute to the success/failure of online learning?" In order to answer this question we need to identify the important variables that (1) measure the learning outcome and (2) can help us understand the learning experience of students using specific learning tools. In this study, the dimensions we explored are student's attitude, affect, motivation and perception of an Online Learning Tool usage. A survey utilizing validated items from previous relevant research work was conducted to help us determine these variables. An exploratory factor analysis (EFA) was used for a basis of our analysis. [ABSTRACT FROM AUTHOR]

Most of the existing computer systems providing technical support for such tests are based on classical logic and therefore cannot reason in the presence of inconsistencies. In this paper we discuss how to assess students' understanding of new terms and concepts applying many-valued logic. This allows an assessment system to give meaningful responses in case of incomplete or inconsistent input. [ABSTRACT FROM AUTHOR]