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Yiran Chen – Research in Higher Education, 2025
The "k"-means clustering method, while widely embraced in college student typology research, is often misunderstood and misapplied. Many researchers regard "k"-means as a near-universal solution for uncovering homogeneous student groups, believing its success hinges primarily on the selection of an appropriate "k."…
Descriptors: College Students, Classification, Educational Research, Research Methodology
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Zarnow, Stefanie; Off, Mona – AERA Online Paper Repository, 2023
Numerous activities and measures can be observed in the context of digitization. However, these are often not interrelated or sufficiently anchored institutionally and structurally with regard to overarching goals. The aim of this study is therefore to carry out a theory-based clustering of connotations with the concept of digit(al)ization in…
Descriptors: Technology Uses in Education, Theories, Adults, Attitudes
Palmer, Bryan – National Centre for Vocational Education Research (NCVER), 2022
This paper summarises the exploratory quantitative analysis undertaken to investigate how vocational education and training (VET) students cluster and segment in the Australian VET market. This analysis is outlined in three sections. The first section focuses on 'clustering' as a technique for grouping data and the three clustering algorithms…
Descriptors: Vocational Education, Foreign Countries, Labor Market, Multivariate Analysis
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Salehudin, Imam; Alpert, Frank – Education & Training, 2022
Purpose: This study analyzed segment differences of student preference for video use in lecture classes and university use of video lecture classes. The authors then conducted novel gap analyses to identify gaps between student segments' preferences for videos versus their level of exposure to in-class videos. Multivariate analysis of variance…
Descriptors: Preferences, Video Technology, Class Activities, College Students
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Nabizadeh, Amir Hossein; Goncalves, Daniel; Gama, Sandra; Jorge, Joaquim – IEEE Transactions on Learning Technologies, 2022
The main challenge in higher education is student retention. While many methods have been proposed to overcome this challenge, early and continuous feedback can be very effective. In this article, we propose a method for predicting student final grades in a course using only their performance data in the current semester. It assists students in…
Descriptors: College Students, Prediction, Grades (Scholastic), Game Based Learning
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Tanja Kovacic; Cormac Forkan – Irish Educational Studies, 2024
Young people who are either at risk of disengaging or disengaged from mainstream education in Ireland are often supported by what is termed 'out-of-school' or the 'alternative education' sector. A recent review of out-of-school education provision (Department of Education. 2022. "Review of Out-of-School Educational Provision." Dublin:…
Descriptors: Foreign Countries, Nontraditional Education, Inclusion, Mainstreaming
Luke Keele; Matthew Lenard; Lindsay Page – Annenberg Institute for School Reform at Brown University, 2021
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Cluster Grouping, Educational Environment, Outcomes of Treatment, Compliance (Psychology)