The development of school education depends on the quality of the education provided, and it is a key metric for assessing the effectiveness of schools in developing talent. Building specialized, intelligent education quality monitoring (EQM) databases is crucial for speeding EQM progress in the big data era. This article examines the development…

This study aims to advance the development of the mathematical processing skills of students by suggesting the use of digital geography games. This includes an analysis of its contribution to the standard mathematics curriculum in areas such as data processing as well as its contribution to social studies curricula in areas such as map literacy,…

Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and…

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…

This article develops a machine learning methodology to analyse the relationship between university accreditation and student experience. It is applied to 98 university accreditations conducted by the Quality Assurance Agency (QAA) in the UK in 2012-2018, and 263,025 university ratings in three categories posted by students on the website…

Artificial intelligence (AI) is a defining technology of the 21st century, creating new opportunities for academic libraries. The goal of this paper is to provide a much-needed analysis, interpreted in an international context, on what the leaders of academic libraries in East-Central Europe, and specifically in Hungary, think about AI and its…

Businesses use data to enhance operational performance, creating demand for professionally trained data/business analytics graduates. Universities offer a variety of academic programs in response to the increasing labor market demands. Yet, research on how well educational offerings adapt to market demand is scant. This paper aims to evaluate how…

Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…

Multimedia information fusion technology is currently a popular technology for data processing. The advanced productivity it brings is dozens of times that of traditional data information processing. The collected and processed information is not only efficient and accurate, but also has strong scalability. With the continuous development of…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Digital technologies have the potential to revolutionize education by enhancing quality, fairness, and efficiency. However, equitable access to these technologies remains a challenge. ILSAs (international large-scale assessments) have shown that the relationship between digital use and performance varies across countries and over time. To fully…

The ongoing 'datafication' of contemporary society has a number of implications for schools and schooling. One is the increasing calls for schools to help develop young people's understandings about the role that digital data now plays in their everyday lives -- especially in terms of the 'data economy' and 'surveillance capitalism'. Reporting on…

Purpose: In this paper, the challenging and thorny issue of assessing graduate attributes (GAs) is addressed. An interdisciplinary team at The University of Alberta -- developed a formative model of assessment centered on students and instructor interaction with course content. Design/methodology/approach: The paper starts by laying the…