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Marpaung, Jonathan – ProQuest LLC, 2021
The shortage of qualified administrators who can utilize data analytics means that institutions are not able to harness data analytics to its fullest potential in order to remain competitive in a higher education market that continued to reward institutions that embrace entrepreneurship. Examining how new student affairs professionals in US higher…
Descriptors: Student Personnel Workers, Entry Workers, Readiness, Data Use
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Alturki, Sarah; Cohausz, Lea; Stuckenschmidt, Heiner – Smart Learning Environments, 2022
The tremendous growth in electronic educational data creates the need to have meaningful information extracted from it. Educational Data Mining (EDM) is an exciting research area that can reveal valuable knowledge from educational databases. This knowledge can be used for many purposes, including identifying dropouts or weak students who need…
Descriptors: Information Retrieval, Data Analysis, Data Use, Prediction
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Gómez-Torres, Emilse – Statistics Education Research Journal, 2021
This paper describes the evolution of "recognition of need for data" and "strategical thinking", two types of thinking identified by Wild and Pfannkuch in their Framework for Statistical Thinking in Empirical Enquiry, as well as its relevance for math teacher professional development. The research was carried out with ten…
Descriptors: Thinking Skills, Mathematics Teachers, Secondary School Teachers, Data Analysis
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Zhao, Yijun; Xu, Qiangwen; Chen, Ming; Weiss, Gary M. – International Educational Data Mining Society, 2020
Predicting student success in a data science degree program is a challenging task due to the interdisciplinary nature of the field, the diverse backgrounds of the students, and an incomplete understanding of the precise skills that are most critical to success. In this study, the applicant's future academic performance in a Master of Data Science…
Descriptors: Grade Prediction, Data Analysis, Masters Programs, Admission Criteria