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Rebeka Man – ProQuest LLC, 2024
In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…
Descriptors: Data, Data Analysis, Data Use, Higher Education
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Rodriguez, AE; Rosen, John – Research in Higher Education Journal, 2023
The various empirical models built for enrollment management, operations, and program evaluation purposes may have lost their predictive power as a result of the recent collective impact of COVID restrictions, widespread social upheaval, and the shift in educational preferences. This statistical artifact is known as model drifting, data-shift,…
Descriptors: Models, Enrollment Management, School Holding Power, Data
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Simsek, Omer; Yazar, Taha – Eurasian Journal of Educational Research, 2016
Problem Statement: The educational technology standards for teachers set by the International Society for Technology in Education (the ISTE Standards-T) represent an important framework for using technology effectively in teaching and learning processes. These standards are widely used by universities, educational institutions, and schools. The…
Descriptors: Educational Technology, Self Efficacy, Validity, Reliability
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Brophy, Caroline; Hahn, Lukas – Journal of Statistics Education, 2014
In this paper, we describe an in-class experiment that is easy to implement with large groups of students. The experiment takes approximately 15-20 minutes to run and involves each student completing one of four types of Sudoku puzzles and recording the time it takes to completion. The resulting data set can be used as a teaching tool at an…
Descriptors: Large Group Instruction, Lecture Method, Educational Experiments, Puzzles