This qualitative study involves six lecturers who have supervised students with disabilities. Participants were purposively selected and interviewed telephonically using semi-structured interviews. The study adopted a thematic data analysis approach to identify patterns in supervision experiences. The paper problematises a deficit approach that is…

This study analyzed students' online assignment submission behaviors from the perspectives of temporal learning analytics. This study aimed to model the time-dependent changes in the assignment submission behavior of university students by employing various machine learning methods. Precisely, clustering, Markov Chains, and association rule mining…

Objective: The purpose of this study was to gain insight about patterns of alcohol use and related consequences among heavy drinking community college students. Participants: About 26 community college students (Mean age 22.3 years, 46% men, 69% White) participated in this study between January and April 2013. Methods: Five qualitative focus group…

This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series…