By studying the use of a virtual learning environment, many have focused on automatically logged web data in order to detect factors that enhance students’ use of the virtual learning environment and that may impact their productive and efficient learning via this means. Following their footsteps, the aim of this research is to examine data (activity logs) obtained by students’ while they are logged into the virtual learning environment in order to detect frequencies and priorities of students’ choice of activities in a virtual learning environment. The activity logs are used to measure students’ effectiveness of learning to determine whether students’ activity logs, within courses supported by a virtual learning environment as part of a blended learning approach, correlate with their final marks and the students’ perceptions of using the virtual learning environment. Observed activities involved course view, assignment view, resource view, forum view, assignment upload and project upload when seen against their final mark. Data log features of a virtual learning environment and an instrument used to gather data on the students’ perceptions of using the virtual learning environment were used. Results show that there are positive correlations between students’ logs of particular activities and their final mark.

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We consider the problem of parameter estimation for an ergodic diffusion with Fisher-Snedecor invariant distribution, to be called Fisher-Snedecor diffusion. We compute the spectral representation of its transition density, which involves a finite number of discrete eigenfunctions (Fisher-Snedecor polynomials) as well as a continuous part. We propose moments based estimators (related to the Fisher-Snedecor polynomials) and prove their consistency and asymptotic normality. Furthermore, we propose a statistical test for the distributional assumptions on the marginal distribution of the Fisher-Snedecor diffusion, based on the moment condition derived from the corresponding Stein's equation.

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