Predicting students at risk of academic failure is valuable for higher education institutions to improve student performance. During the pandemic, with the transition to compulsory distance learning in higher education, it has become even more important to identify these students and make instructional interventions to avoid leaving them behind. This goal can be achieved by new data mining techniques and machine learning methods. This study took both the synchronous and asynchronous activity characteristics of students into account to identify students at risk of academic failure during the pandemic. Additionally, this study proposes an optimal ensemble model predicting students at risk using a combination of relevant machine learning algorithms. Performances of over two thousand university students were predicted with an ensemble model in terms of gender, degree, number of downloaded lecture notes and course materials, total time spent in online sessions, number of attendances, and quiz score. Asynchronous learning activities were found more determinant than synchronous ones. The proposed ensemble model made a good prediction with a specificity of 90.34%. Thus, practitioners are suggested to monitor and organize training activities accordingly.
This paper was checked for plagiarism using iThenticate during the preview process and before publication. / Bu çalışma ön inceleme sürecinde ve yayımlanmadan önce iThenticate yazılımı ile taranmıştır.
In the life of students who are named digitally born in this era, tablets have a crucial role. The aim of this study, which is designed as a case study model, is to determine the use of tablet by second grade students and it aims to reveal their perception towards tablets via metaphors. 63-second grade students are participated in this study in spring semester in 2015-2016 in Muğla regarding convenient sampling method. The data for the study is gathered via a written form including students' background information and open-ended questions that is developed by the researchers of this study. The data are analyzed via content analysis methods. As a result of the study, it is determined that parents mostly restrict the use of tablets by their children; moreover students prefer reading printed books to digital ones and they prefer playing with their friends in parks to playing games in their tablets; additionally it is determined that the students in this study use tablets for the aim of playing games, searching, watching videos and doing homework, however they rarely use tablets in order to read books, listen to music and take photographs. Besides, it is seen that the students have a positive aspect for using tablets, and they develops 24 metaphors under 4 main themes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.