With the wide spread of massive open online courses ( MOOC ), millions of people have enrolled in many courses, but the dropout rate of most courses is more than 90%. Accurately predicting the dropout rate of MOOC is of great significance to prevent...
(1) Background: Measles remains a major cause of disease and death worldwide, especially in the World Health Organization African Region. This study aimed to estimate the coverage of measles vaccinations and map the spatial distribution of measles va...
Background/Objectives: Virtual reality has emerged as a promising intervention for pain management in individuals with cancer. Although its clinical effects have been explored, little is known about participant adherence and dropout behavior. This sy...
Background/Objectives: Exercise has gained attention as a potentially beneficial non-pharmacological intervention, but whether this type of intervention presents a higher dropout rate compared to other interventions is still unknown. This systematic...
School dropout and the recruitment of minors by criminal organizations have become deeply intertwined phenomena in Ecuador, particularly in territories marked by extreme violence and institutional fragility. This study investigates how Ecuadorian nat...
The prediction of university dropout is a complex problem, given the number and diversity of variables involved. Therefore, different strategies are applied to understand this educational phenomenon, although the most outstanding derive from the join...
Student dropout remains a persistent challenge for higher education systems, with consequences for student trajectories, institutional efficiency, and equity. This study investigates the relationship between student dropout propensity and academic en...
The growing dropout and low permanence of rural students in higher education has become a central problem in the education system, both affecting the quality conditions of training programmes and preventing the materialisation of the benefits that ac...
High and persistent dropout rates represent one of the biggest challenges for improving the efficiency of the educational system, particularly in underdeveloped countries. A range of features influence college dropouts, with some belonging to the edu...
University dropout remains a critical challenge in South Korean higher education, with over 100,000 students leaving annually. This study investigates the structural and institutional factors influencing dropout rates across 211 four-year universitie...
The dropout rate is one of the determinants of immunization coverage and program performance, program continuity, and follow-up. The dropout rate refers to the proportion of vaccine recipients who did not finish their vaccination schedules, and it is...
This work reports and discusses the results of a secondary analysis on statistical data regarding the phenomenon of school dropout in Italy starting from primary school. The research was conducted as part of Next GenerationEU funded by the European U...
A data-driven method to identify frequent sets of course failures that students should avoid in order to minimize the likelihood of their dropping out from their university training is proposed. The overall probability distribution of the dropout is...
The aim of this study is to identify the key factors contributing to student dropout and to develop a predictive model that estimates the dropout risk of students based on their entry characteristics and enrolment registration data. Our analysis is b...
Academic dropout is a persistent challenge in higher education, particularly in contexts with socio-economic disparities and diverse learning conditions. Traditional predictive models often fail to capture the complex, non-linear interactions underly...
In Colombia, the gaps of regional inequalities and social opportunities permeate people’s economic, political, and social participation. Additionally, the initial endowments of individual and socioeconomic background, barriers to financial aid,...
Massive Open Online Courses (MOOCs) have expanded global access to education but continue to struggle with high attrition rates. This study presents a comparative analysis of self-labeled Semi-Supervised Learning (SSL) algorithms for predicting learn...
Background/Objectives: The increasing adoption of laparoscopic liver resection (LLR) and changes in clinical management may influence access to curative treatments for patients on the liver transplant waiting list. We aimed to analyze temporal trends...
Massive Open Online Courses (MOOCs) are a relatively new educational model that provides free access to educational content regardless of location or time. Despite these benefits, MOOCs encounter significant challenges, such as low completion rates,...
Computer science is a dynamic field of study that requires constant review and updating of the curricular designs in academic programs—in general, measuring the impact of plan changes has been little explored in the literature. In most cases, i...
More and more researchers use single-cell RNA sequencing (scRNA-seq) technology to characterize the transcriptional map at the single-cell level. They use it to study the heterogeneity of complex tissues, transcriptome dynamics, and the diversity of...
Student dropout represents a significant challenge for the sustainability of higher education systems, particularly in regional public contexts where academic trajectories are heavily shaped by socioeconomic conditions. While prior research typically...
Cognitive study strategies and motivational orientations play a crucial role in promoting successful learning and academic achievement. This study aims to explore the presence of different cognitive–motivational profiles among Italian universit...
Deep neural networks are often susceptible to overfitting, necessitating effective regularization techniques. This paper introduces Spectral Adaptive Dropout, a novel frequency-based regularization technique that dynamically adjusts dropout rates bas...
Learning patterns are crucial for predicting student dropout in educational settings, providing insights into students’ behaviors and motivations. However, existing mainstream dropout prediction models have limitations in effectively mining the...
This research presents the development of a predictive model to address student dropout in higher education, using advanced artificial intelligence techniques, specifically in the field of machine learning. To this end, the CRISP-DM methodology is fo...
Background: Glaucoma is a multifactorial optic neuropathy and the leading cause of irreversible blindness worldwide. Vascular mechanisms, including impaired perfusion of the optic nerve head, are increasingly recognized as contributors to disease pro...
This paper begins by exploring the challenge of event-triggered state estimations in nonlinear systems, grappling with packet dropout and correlated noise. A communication mechanism is introduced that determines whether to transmit measurement values...
The phenomenon of student dropout in higher education presents significant challenges for students, higher education institutions, governments, and society. The present study focuses on the dropout rates within the engineering programmes at one schoo...
Research interest in massive online and open courses (MOOCs) is rapidly growing, questioning who enrolls, why and how to conceive engagement, and success rates. This study is focused on MOOC-takers behavior obtained from a seven-week MOOC experience...
Heart failure (HF) is a growing epidemic, affecting millions of people worldwide, and is a major cause of mortality, morbidity, and impaired quality of life. Traditional cardiac rehabilitation is a valuable approach to the physical and quality-of-lif...
Passion for studying represents a crucial motivational resource in students’ academic functioning, yet its role remains complex. Based on Vallerand’s dualistic model of passion, this paper examines how harmonious and obsessive study passi...
Academically resilient students achieve high performance despite socioeconomic disadvantages. Although this population has received increasing attention, little is known about its motivational heterogeneity, a critical gap given the central role of m...
This work proposes a methodology for the automated sizing of transistors in analog integrated circuits, based on a modular and hierarchical representation of the circuit. The methodology combines structured design techniques and systematic design flo...
The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history...
This paper describes a nationwide learning analytics initiative in Uruguay focused on the future implementation of governmental policies to mitigate student retention and dropouts in secondary education. For this, data from a total of 258,440 student...
Background: Despite remarkable progress in expanding access to childhood vaccines in the last two decades, global coverage with the third dose of the diphtheria–tetanus–pertussis-containing vaccine (DTP3) has recently plateaued, with many...
Background/Objectives: Adherence to active physiotherapy programs in children suffering from cancer is essential to enhance the improvement generated by the treatment. Therefore, the main aim of this review was to identify the factors influencing adh...
Student dropout, defined as the abandonment of a high education program before obtaining the degree without reincorporation, is a problem that affects every higher education institution in the world. This study uses machine learning models over two C...
While high dropout rates hinder the success of online education, little is known about the patterns of dropout beyond adult education, particularly regarding time-related variables. This study aims to address this gap by analyzing data from 219 onlin...
Since the first SARS-CoV-2 outbreak, mutations such as single nucleotide polymorphisms (SNPs) and insertion/deletions (INDELs) have changed and characterized the viral genome sequence, structure and protein folding leading to the onset of new variant...
Since a high dropout rate for university students is a significant risk to local communities and countries, a dropout prediction model using machine learning is an active research domain to prevent students from dropping out. However, it is challengi...
24 April 2025
Mental health problems among university students have become a growing concern for higher education institutions. Students experiencing mental health issues, with depression being the most prevalent disorder, tend to take longer to graduate and have...
Dropout prediction is a problem that must be addressed in various organizations, as retaining customers is generally more profitable than attracting them. Existing approaches address the problem considering a dependent variable representing dropout o...
This paper presents a Dynamic Adam and dropout based deep neural network (DADDNN) for fault diagnosis of oil-immersed power transformers. To solve the problem of incomplete extraction of hidden information with data driven, the gradient first-order m...
Mine water inflow is a significant safety concern in coal mine operations. Accurately predicting the volume of mine water inflow is vital for ensuring mine safety and environmental protection. This study focused on the Laohutai mining area in Liaonin...
The school context, following an overall complexification of society, presents several situations in which it is necessary to build a transformative setting based on the suspension of educational action and the use of in-depth interpretations of dive...
Data-driven algorithms have been widely applied in predicting tool wear because of the high prediction performance of the algorithms, availability of data sets, and advancements in computing capabilities in recent years. Although most algorithms are...
University dropout is a phenomenon that is a concern in many countries all over the world. However, although there are studies in which the direct relationship of the personal and contextual variables is observed individually to predict dropout, ther...
The study of gender markers is essential in forensic genetic analysis. Mutations in the X or Y homologs of the amelogenin gene can be misleading, resulting in serious mistakes in forensic genetic analysis. We recently discovered two male cases of the...
of 12