With the emergence of Artificial Intelligence (AI), smart education has become an attractive topic. In a smart education system, automated classrooms and examination rooms could help reduce the economic cost of teaching, and thus improve teaching efficiency. However, existing AI algorithms suffer from low surveillance accuracies and high…

This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

Team has been widely applied in various fields, in which the collaboration efficiency of a team is the main consideration under the constraints of skill requirements. In educational scenarios, an educational institution usually builds a team of students with different skills to attend a competition, in which team communication cost and team…

This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners' responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent…

Although self-regulated learning (SRL) plays an important role in supporting online learning performance, the lack of student self-regulation skills poses a persistent problem to many educators. Recommender systems have the potential to promote SRL by delivering personalized feedback and tailoring learning strategies to meet individual learners'…

As is rapidly becoming clear, data science increasingly permeates many aspects of life. Educational research recognizes the importance and complexity of learning data science. In line with this imperative, there is a growing need to investigate the factors that influence student performance in data science tasks. In this paper, we aimed to apply…

Emotions of learners are fundamental and significant in e-learning as they encourage learning. Machine learning models are presented in the literature to look at how emotions may affect e-learning results that are improved and optimized. Nevertheless, the models that have been suggested so far are appropriate for offline mode, whereby data for…

Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…

Online learning continues to expand due to globalization and the COVID-19 pandemic. However, maintaining student engagement in this new normal has become increasingly difficult. Conventional techniques, such as self-reports and manual observations, often fall short of capturing the subtle behaviors that indicate attentiveness. This emphasizes the…

To be an effective teacher, one must possess strong learning abilities. Developing lesson planning, pursuing learning objectives, and assessing post-lesson accomplishments all these depend on reflection and ongoing learning. As education is context-specific, the iterative process of preparing, reflecting, and improving is what makes teaching…

In the context of massive open online courses (MOOCs), searching and retrieving information can be challenging because there is a huge amount of unstructured content, which creates a problem and makes it difficult for users to quickly find relevant lessons or resources. As a result, learners and teachers face significant barriers to accessing the…

The rapid advancement of digital technologies is prompting a necessary shift in traditional educational models, particularly in finance education. This study introduces the "Multi-Dimensional Situated Learning Model" (MD-SLM), which is rooted in constructivist theory and aims to enhance teaching strategies in university finance courses.…

The proliferation of digital learning platforms has revolutionized the generation, accessibility, and dissemination of educational resources, fostered collaborative learning environments and producing vast amounts of interaction data. Machine learning (ML) algorithms have emerged as powerful tools for analyzing these complex datasets, uncovering…

Video summarization is a method of deducing the content of video content for generating a summary in video format. The generated summary should have the significant segments of raw video. Recently, the content of video has been rapidly increasing, thus automatic video summarization is beneficial for individuals who want to keep time and learn more…

Predicting student performance in international large-scale assessments (ILSAs) is crucial for understanding educational outcomes on a global scale. ILSAs, such as the Program for International Student Assessment and the Trends in International Mathematics and Science Study, serve as vital tools for policymakers, educators, and researchers to…