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Direct linkScholes, Vanessa – Educational Technology Research and Development, 2016
There are good reasons for higher education institutions to use learning analytics to risk-screen students. Institutions can use learning analytics to better predict which students are at greater risk of dropping out or failing, and use the statistics to treat "risky" students differently. This paper analyses this practice using…
Descriptors: Data Collection, Data Analysis, Educational Research, At Risk Students
Cohen, Anat – Educational Technology Research and Development, 2017
Persistence in learning processes is perceived as a central value; therefore, dropouts from studies are a prime concern for educators. This study focuses on the quantitative analysis of data accumulated on 362 students in three academic course website log files in the disciplines of mathematics and statistics, in order to examine whether student…
Descriptors: Academic Persistence, Predictor Variables, Dropouts, At Risk Students
Joo, Young Ju; Kim, Nari; Kim, Nam Hee – Educational Technology Research and Development, 2016
This study analyzed the relationships among factors predicting online university students' actual usage of a mobile learning management system (m-LMS) through a structural model. Data from 222 students in a Korean online university were collected to investigate integrated relationships among their perceived ease of use, perceived usefulness,…
Descriptors: Foreign Countries, College Students, Integrated Learning Systems, Handheld Devices
Ifenthaler, Dirk; Schumacher, Clara – Educational Technology Research and Development, 2016
The purpose of this study was to examine student perceptions of privacy principles related to learning analytics. Privacy issues for learning analytics include how personal data are collected and stored as well as how they are analyzed and presented to different stakeholders. A total of 330 university students participated in an exploratory study…
Descriptors: Student Attitudes, Privacy, Data Collection, Data Analysis
