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CNN autoencoders and LSTM-based reduced order model for student dropout prediction
In recent years, Massive Open Online Courses (MOOCs) have become the main online learning method for students all over the world, but their...
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Investigating the Predictive Potential of Large Language Models in Student Dropout Prediction
In the landscape of educational analytics, the usage of Machine Learning (ML), Deep Learning (DL), and Survival Analysis (SA), for student dropout...
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Data Collection and Pre-processing for Machine Learning-Based Student Dropout Prediction
In this era of big data, a large amount of data is generated from various educational environments that will help integrate machine learning...
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Student Dropout Analysis in Higher Education and Retention by Artificial Intelligence and Machine Learning
Student dropouts are a long-standing, substantial issue in academia that has never received meaningful attention globally. Numerous research studies...
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Dropout in online higher education: a systematic literature review
The increased availability of technology in higher education has led to the growth of online learning platforms. However, a significant concern...
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A machine learning based model for student’s dropout prediction in online training
School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a...
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Predicting School Dropout in Malawi
School dropout is a significant issue, especially in develo** countries due to high poverty levels and inadequate allocation of resources to...
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Learning behavior feature fused deep learning network model for MOOC dropout prediction
Massive open online courses (MOOCs) have become one of the most popular ways of learning in recent years due to their flexibility and convenience....
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Analyzing College Student Dropout Risk Prediction in Real Data Using Walk-Forward Validation
College dropout is a concern for educational institutions since it directly impacts educational management and academic results, as well as being...
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Interpretable Dropout Prediction: Towards XAI-Based Personalized Intervention
Student drop-out is one of the most burning issues in STEM higher education, which induces considerable social and economic costs. Using machine...
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Negative link prediction to reduce dropout in Massive Open Online Courses
In recent years, the rapid growth of Massive Open Online Courses (MOOCs) has attracted much attention for related research. Besides, one of the main...
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A hybrid approach for early-identification of at-risk dropout students using LSTM-DNN networks
Dropout refers to the phenomenon of students leaving school before completing their degree or program of study. Dropout is a major concern for...
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A methodology to design, develop, and evaluate machine learning models for predicting dropout in school systems: the case of Chile
School dropout is a structural problem which permanently penalizes students and society in areas such as low qualification jobs, higher poverty...
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Analyzing the relation among different factors leading to Ph.D. dropout using numerical association rule mining
Ph.D. dropout is a persistent and challenging issue in higher education, with significant implications for individual students, academic...
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A nonlinear state space model predicting dropout: the case of special education students in the Hellenic Open University
While open and distance education gains growing recognition over time, it also faces increasing drop-out rates. Consequently, the development of...
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MOOC Dropout Prediction Based on Bayesian Network
High dropout rates and unsatisfactory learning outcomes have become the main problems of MOOC platforms, and the intervention of dropout prediction...
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Adaptive-CSSA: adaptive-chicken squirrel search algorithm driven deep belief network for student stress-level and drop out prediction with MapReduce framework
Stress is correlated with various illnesses that include diabetes, depression, and other chronic diseases and plays an important role in the...
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Heuristic Technique to Find Optimal Learning Rate of LSTM for Predicting Student Dropout Rate
Predictive analytics is being increasingly recognized as being important for evaluating university students’ academic achievement. Utilizing big data...
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School Dropout Prediction with Class Balancing and Hyperparameter Configuration
School dropout and academic underachievement have significant effects on economic growth and employment in society. This phenomenon impacts not only...
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A stacking ensemble machine learning method for early identification of students at risk of dropout
Early dropout of students is one of the bigger problems that universities face currently. Several machine learning techniques have been used for...
