The purpose of the study on which this paper is based was to conduct a performance evaluation of student learning for an introductory course in project management in a higher educational institution in Norway. This was done by utilizing performance m...
Student performance predictive analysis has played a vital role in education in recent years. It allows for the understanding students’ learning behaviours, the identification of at-risk students, and the development of insights into teaching a...
The prediction of student academic performance has drawn considerable attention in education. However, although the learning outcomes are believed to improve learning and teaching, prognosticating the attainment of student outcomes remains underexplo...
Transferring knowledge from one domain to another has gained a lot of attention among scientists in recent years. Transfer learning is a machine learning approach aiming to exploit the knowledge retrieved from one problem for improving the predictive...
Intelligent recommender systems are essential for identifying at-risk students and personalizing learning through tailored resources. Accurate prediction of student performance enables these systems to deliver timely interventions and data-driven sup...
The rapid growth of online learning platforms has intensified the need for privacy-aware methods that can analyze learner behavior without centralizing sensitive activity logs. This study presents a Federated Learning-Based Graph Representation Learn...
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environm...
Success in student learning is the primary aim of the educational system. Artificial intelligence utilizes data and machine learning to achieve excellence in student learning. In this paper, we exploit several machine learning techniques to estimate...
Federated learning can support privacy-conscious student performance prediction by enabling collaborative model training across educational institutions without centralizing sensitive student records. However, existing educational federated learning...
As an emerging teaching method, online learning is becoming increasingly popular among learners. However, one of the major drawbacks of this learning style is the lack of effective communication and feedback, which can lead to a higher risk of studen...
Using Machine Learning (ML) in educational management transforms higher education strategy. This study examines students’ views on machine learning (ML) technologies and how they might be used to plan, monitor, and predict student performance....
Accurate and interpretable prediction of student academic performance is a cornerstone of data-driven educational support systems, enabling timely interventions, personalized learning pathways, and equitable resource allocation. While ensemble machin...
This study addresses fairness in machine learning for student academic performance prediction using the UCI Student Performance dataset. We comparatively evaluate logistic regression, Random Forest, and XGBoost, integrating the Synthetic Minority Ove...
The 21st century has seen dramatic changes to education delivery which have widened the scope of transnational education and remote learning via various virtual learning environments (VLEs). Efficient remote teaching activities require students to be...
The objective of this research is to develop an machine learning (ML) -based system that evaluates the performance of high school students during the semester and identify the most significant factors affecting student performance. It also specifies...
Improving the quality, developing and implementing systems that can provide advantages to students, and predicting students’ success during the term, at the end of the term, or in the future are some of the primary aims of education. Due to its...
Technology and innovation empower higher educational institutions (HEI) to use different types of learning systems—video learning is one such system. Analyzing the footprints left behind from these online interactions is useful for understandin...
This study examines how interaction data from Learning Management Systems (LMSs) can be leveraged to predict student performance and enhance academic outcomes through personalized study plans tailored to individual learning styles. The research follo...
In 2019, the TIMSS study offered a closer look at how Moroccan eighth-grade students were doing in mathematics. The data came from a sample of 8390 students; 37% performed well, while the remaining 63% struggled. The goal was to better understand whi...
The Leadership for Learning (LfL) framework is often used to investigate the effect of leadership on student achievement (SA). This framework encompasses instructional leadership (IL), transformational leadership (TL), and distributed leadership (DL)...
This study aims to predict and discover important factors for the learning performance of students belonging to two ethnic groups—Khmer and Chinese (Hoa) students—in Soc Trang with the use of random forest (RF) and Gaussian Naïve Bay...
Electronic learning management systems provide live environments for students and faculty members to connect with their institutional online portals and perform educational activities virtually. Although modern technologies proactively support these...
The identification of heterogeneous and homogeneous groups of students using clustering analysis in learning analytics is still rare. The paper describes a study in which the students’ performance data stored in the micro-learning platform Pris...
This study examines how the gender of students and their level of education (undergraduate or postgraduate students) influence affective learning outcomes in a mixed environment. The research model is based on four key indicators: satisfaction, perce...
Predicting students’ performance is one of the most important topics for learning contexts such as schools and universities, since it helps to design effective mechanisms that improve academic results and avoid dropout, among other things. Thes...
The learning performance of international students and students with disabilities has increasingly attracted many theoretical and practical researchers. However, previous studies used questionnaires, surveys, and/or interviews to investigate factors...
Affective and cognitive factors play significant roles in influencing students’ learning performance. However, limited studies exist that examine the latent interactions between these factors and students’ learning performance. This study...
Universities and schools rely heavily on the ability to forecast student performance, as it enables them to develop efficient strategies for enhancing academic results and averting student attrition. The automation of processes and the management of...
University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, due to the COVID-19 pandemic. This type of education is significant because it ensures that all students receive the required learning. The statistical e...
Understanding students’ learning processes and education-related phenomena by extracting knowledge from educational data sets represents a continuous interest in the educational data mining domain. Due to an accelerated expansion of online learning a...
In this paper, we investigated the impact of an early learning assessment on students’ motivation for improving their performance throughout the semester. An observation analysis was conducted on an entry level mechanical engineering course in...
For the majority of people, bursaries are a significant concern during their academic careers. This research focuses on how satisfied subsidized students are with the program and how it affects their ability to learn after receiving disadvantaged stu...
Digital transformation is reshaping technical and vocational education and training (TVET), yet the behavioral processes through which students’ digital learning competence is associated with learning performance remain underexplored. Drawing o...
The study of learning analytics provides statistical analysis and extract insights from data, particularly in education. Various studies regarding student engagement in online learning have been conducted at tertiary institutions to verify its effect...
University students often face challenges in managing academic demands and difficulties like time management, task prioritization, and effective study strategies. This scoping review investigates the application of Deep Learning (DL) and Reinforcemen...
With the rapid spread of COVID-19 worldwide, governments of all countries declared the closure of educational institutions to control its transmission. As a result, institutions were under pressure to offer online education opportunities so that stud...
In non-English-speaking countries, students learning EFL (English as a Foreign Language) without a “real” learning environment mostly shows poor English-learning performance. In order to improve the English-learning effectiveness of EFL s...
27 January 2019
The influence of learning approaches, the styles of self-regulation that the student considers in his academic task (self-regulation before, during and after the task) and the perceived academic self-efficacy of university students in their academic...
During the pandemic, universities were forced to convert their educational process online. Students had to adapt to new educational conditions and the proposed online environment. Now, we are back to the traditional blended learning environment and w...
Despite the rapid adoption of bilingual programs (English–Chinese) in Chinese higher education institutions (HEIs), concerns have been raised about perceived language hindrance to students’ academic comprehension and performance. In respo...
Virtual learning environment (VLE) is vital in the current age and is being extensively used around the world for knowledge sharing. VLE is helping the distance-learning process, however, it is a challenge to keep students engaged all the time as com...
7 November 2022
Previous studies have revealed the restorative effects of exposure to natural environments on psychological well-being and cognitive performance. Recent studies have reported the effects of exposure to nature sounds (e.g., the sounds of birds, rainfa...
Due to COVID-19, the researching of educational data and the improvement of related systems have become increasingly important in recent years. Educational institutions seek more information about their students to find ways to utilize their talents...
The study explores the application of data analytics and machine learning to forecast academic outcomes, with the aim of ensuring effective and sustainable e-learning. Technological study programs in universities often experience high dropout rates,...
This research investigates the impact of digital math serious educational games (SEGs) on enhancing math skills and motivation, specifically focusing on first-degree equations for students with learning difficulties. A comparative study was conducted...
The long-lasting pandemic has disrupted face–to–face education and has forced higher education institutions to adopt digital learning management systems, albeit many public universities in developing counties could not properly undertake...
The purpose of this study is to examine the effects of middle school students’ learning attitudes and risk perception toward COVID-19 on their poor academic performance since the COVID-19 pandemic began. This study limited the sample to middle school...
Educational institutions are increasingly focused on supporting students who may be facing academic challenges, aiming to enhance their educational outcomes through targeted interventions. Within this framework, leveraging advanced deep learning tech...
Background: The COVID-19 pandemic caused all universities in Malaysia to switch to online learning, including for dental education. The effect of this switch has yet to be assessed. Thus, this study aimed to assess International Islamic University Ma...
Predicting students’ performance is one of the most important issues in educational data mining. In this study, a method for representing students’ partial sequence of learning activities is proposed, and an early prediction model of stud...
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