相关论文: Students Success Modeling: Most Important Factors

Supporting student success requires collaboration among multiple stakeholders. Researchers have explored machine learning models for academic performance prediction; yet key challenges remain in ensuring these models are interpretable,…

The high level of attrition and low rate of certification in Massive Open Online Courses (MOOCs) has prompted a great deal of research. Prior researchers have focused on predicting dropout based upon behavioral features such as student…

The prediction of academic dropout, with the aim of preventing it, is one of the current challenges of higher education institutions. Machine learning techniques are a great ally in this task. However, attention is needed in the way that…

Identification of patients at high risk for readmission could help reduce morbidity and mortality as well as healthcare costs. Most of the existing studies on readmission prediction did not compare the contribution of data categories. In…

A growing number of universities worldwide use various forms of online and blended learning as part of their academic curricula. Furthermore, the recent changes caused by the COVID-19 pandemic have led to a drastic increase in importance…

Not everyone who enrolls in college will leave with a certificate or degree, but the number of people who drop out or take a break is much higher than experts previously believed. In December 2013, there were 29 million people with some…

Post-secondary education persistence is the likelihood of a student remaining in post-secondary education. Although statistics show that post-secondary persistence for deaf students has increased recently, there are still many obstacles…

The purpose of this study is to explore students' backtracking patterns in using a digital textbook and reveal the relationship between backtracking behaviors and academic performance as well as learning styles. The study was carried out…

Student dropout is a significant concern for educational institutions due to its social and economic impact, driving the need for risk prediction systems to identify at-risk students before enrollment. We explore the accuracy of such…

Detecting abnormal behaviors of students in time and providing personalized intervention and guidance at the early stage is important in educational management. Academic performance prediction is an important building block to enabling this…

In this paper, we compare predictive models for students' final performance in a blended course using a set of generic features collected from the first six weeks of class. These features were extracted from students' online homework…

Evaluation of students' performance for the completion of courses has been a major problem for both students and faculties during the work-from-home period in this COVID pandemic situation. To this end, this paper presents an in-depth…

While academic metrics such as transcripts and GPA are commonly used to evaluate students' knowledge acquisition, there is a lack of comprehensive metrics to measure their preparedness for the challenges of post-graduation life. This…

Depression is a common yet serious mental disorder that affects millions of U.S. high schoolers every year. Still, accurate diagnosis and early detection remain significant challenges. In the field of public health, research shows that…

Dropout in higher education is commonly analysed through observable academic events such as course failure or repetition. However, these event-based perspectives may obscure the underlying structural dynamics that shape student…

Prediction tasks about students have practical significance for both student and college. Making multiple predictions about students is an important part of a smart campus. For instance, predicting whether a student will fail to graduate…

Predictive analytics is widely used in learning analytics, but many resource-constrained institutions lack the capacity to develop their own models or rely on proprietary ones trained in different contexts with little transparency. Transfer…

Choosing the right and effective way to assess students is one of the most important tasks of higher education. Many studies have shown that students tend to receive higher scores during their studies when assessed by different study…

Student performance modelling (SPM) is a critical step to assessing and improving students performances in their learning discourse. However, most existing SPM are based on statistical approaches, which on one hand are based on probability,…

STEM dropout rates remain high at universities, particularly in computer science programs with theory-intensive courses. Digital learning environments now capture rich behavioral data that could help identify struggling students early, yet…