Learning analytic models are built upon traces students leave in technology-enhanced learning platforms as the digital footprints of their learning processes. Learning analytics uses these traces of learning engagement to predict performance and provide learning feedback to students and teachers when these predictions signal the risk of failing a…

In the paper, we present the results of a case study conducted at Faculty of Administration, University of Ljubljana among 1st year undergraduate students. We investigated the correlations between students' activities in the e-classroom and grades at the final exam. The sample included 92 participants who took part at the final exam in the course…

Blended learning is already a strongly established way of teaching in higher education. In support of face-to-face teaching, e-courses may vary in structure, assignments, prompt examinations, interaction between students and teachers etc. In the paper, we present an analysis of factors that influence the usefulness of e-courses as perceived by…

This study investigated whether college students' self-efficacy, level of learning strategy use, academic burnout, and school support predict course satisfaction and learning persistence. To this end, self-efficacy, level of learning strategy use, academic burnout, and school support were used as prediction variables, and course satisfaction and…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…