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Agus Santoso; Heri Retnawati; Kartianom; Ezi Apino; Ibnu Rafi; Munaya Nikma Rosyada – Open Education Studies, 2024
The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…
Descriptors: Time to Degree, Open Universities, Foreign Countries, Predictive Measurement
Melisa Diaz Lema; Melvin Vooren; Marta Cannistrà; Chris van Klaveren; Tommaso Agasisti; Ilja Cornelisz – Studies in Higher Education, 2024
Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students' dropout based on an integrated…
Descriptors: Foreign Countries, Dropout Research, College Students, Dropouts
Cláudio Manoel Ferreira Leite; Herbert Ugrinowitsch; Crislaine Rangel Couto – Journal of Motor Learning and Development, 2024
Knowledge of results (KR), particularly its informational role, has often been regarded as redundant for learning interception-like tasks, such as coincidence-anticipation timing tasks. However, it is possible that the KR's guiding effect might be detrimental to motor adaptation, instead of only redundant, leading to a dependency on KR and…
Descriptors: Foreign Countries, Undergraduate Students, Psychomotor Skills, Motor Development
James T. Davis; Kristina Adams; Ashley Morgan – Advances in Physiology Education, 2024
Assessing student mastery is often done by using exams. Inevitably, some students will complete remediation, which may include exam retakes. This method provides students an additional opportunity to take an exam that assesses the same objectives as the original exam, while using different questions. Although this form of remediation increases…
Descriptors: Undergraduate Students, Public Colleges, Physiology, Test Preparation
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – AERA Open, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Identification, Two Year College Students, Community Colleges
Naseem, Mohammed; Chaudhary, Kaylash; Sharma, Bibhya – Education and Information Technologies, 2022
The need for a knowledge-based society has perpetuated an increasing demand for higher education around the globe. Recently, there has been an increase in the demand for Computer Science professionals due to the rise in the use of ICT in the business, health and education sector. The enrollment numbers in Computer Science undergraduate programmes…
Descriptors: College Freshmen, Student Attrition, School Holding Power, Dropout Prevention
Yamamoto, Scott H.; Alverson, Charlotte Y. – Autism & Developmental Language Impairments, 2022
Background and Aims: The fastest growing group of students with disabilities are those with Autism Spectrum Disorder (ASD). States annually report on post-high school outcomes (PSO) of exited students. This study sought to fill two gaps in the literature related to PSO for exited high-school students with ASD and the use of state data and…
Descriptors: Autism Spectrum Disorders, Students with Disabilities, High School Graduates, Outcomes of Education
Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics
Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
Kyle R. Siddoway – ProQuest LLC, 2021
Acts of targeted violence are of great concern to college administrators. Additionally, targeted violence motivated by bias (e.g., racism, sexism, homophobia, xenophobia, etc.) is occurring at an increasing rate on campuses across the country. Previous research has identified potential pre-incident behaviors which may serve as indicators that an…
Descriptors: College Students, Student Behavior, School Violence, Aggression
Chen, Yu; Upah, Sylvester – Journal of College Student Retention: Research, Theory & Practice, 2020
Science, Technology, Engineering, and Mathematics student success is an important topic in higher education research. Recently, the use of data analytics in higher education administration has gain popularity. However, very few studies have examined how data analytics may influence Science, Technology, Engineering, and Mathematics student success.…
Descriptors: STEM Education, Academic Advising, Data Analysis, Majors (Students)
Kayri, Murat – Educational Sciences: Theory and Practice, 2015
The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…
Descriptors: Artificial Intelligence, Influences, Academic Achievement, College Students
Dehan, Jamie – ProQuest LLC, 2018
Purpose: The purpose of this study was to examine the effect professional foundational physical therapist education program coursework variables have in predicting National Physical Therapy Examination (NPTE) scores. This study examined variables including Anatomy course grade, Biomechanics/Kinesiology course grade, Exercise Physiology course…
Descriptors: Physical Therapy, Allied Health Occupations Education, Predictive Measurement, Licensing Examinations (Professions)
Hao, Jinmei; Li, Suke – Journal of Education and Practice, 2017
With the adjustment of industrial structure of China in recent years, the market urgently needs different levels of professionals. Specialty education is an important part of higher education in China, has its unique advantages. Through the analysis of the history data of specialty education in our country, the result shows that the specialty…
Descriptors: Foreign Countries, Specialization, Specialists, Enrollment Trends