The study of learning behaviors with multi features is of great significance for interactive cooperation. The data prediction and decision are to realize the comprehensive analysis and value mining. In this study, hierarchical learning behavior based on feature cluster is proposed. Based on the massive data in interactive learning environment, the…

Higher education institutions in the UK have organised into mission groups for the advocacy of shared interests and ideologies. Although research productivity is claimed as a key point of difference between these groups, this claim has received relatively little empirical scrutiny. The current study examined the clustering of UK universities based…

In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…

Data transfer between isolated clusters is imperative for cybersecurity education, research, and testing. Such techniques facilitate hands-on cybersecurity learning in isolated clusters, allow cybersecurity students to practice with various hacking tools, and develop professional cybersecurity technical skills. Educators often use these remote…

Analysis of the differential treatment effects across targeted subgroups and contexts is a critical objective in many evaluations because it delineates for whom and under what conditions particular programs, therapies or treatments are effective. Unfortunately, it is unclear how to plan efficient and effective evaluations that include these…

The exponential growth of scholarly publications in recent years has presented a daunting challenge for researchers to keep track of relevant articles within their research field. To address this issue, we examined the capabilities of InfraNodus, an AI-Powered text network analysis platform. InfraNodus promises to provide insights into any…

Purpose: Nonnative consonant cluster learning has become a useful experimental approach for learning about speech motor learning, and we sought to enhance our understanding of this area and to establish best practices for this type of research. Method: One hundred twenty individuals completed a nonnative consonant cluster learning task within a…

Numerous activities and measures can be observed in the context of digitization. However, these are often not interrelated or sufficiently anchored institutionally and structurally with regard to overarching goals. The aim of this study is therefore to carry out a theory-based clustering of connotations with the concept of digit(al)ization in…

For decades, cluster initiatives and funding programmes have been used as instruments of industrial and innovation policy--addressing system failures by strengthening linkages among actors, fostering innovation, and developing more effective innovation systems. More recently, a growing segment of these initiatives are also focused on driving…

This paper summarises the exploratory quantitative analysis undertaken to investigate how vocational education and training (VET) students cluster and segment in the Australian VET market. This analysis is outlined in three sections. The first section focuses on 'clustering' as a technique for grouping data and the three clustering algorithms…

The purpose of this study was to examine clusters of less-skilled college readers. College students with below average reading comprehension skills (N = 77) read and thought aloud about four texts, recalled the texts, and completed standardized assessments of reading skills. Based on the findings of cluster analyses of the cognitive processes…

Objectives: To determine whether first-year college students cluster in networks based on subjective perceptions of loneliness. Participants: 492 first-year Notre Dame students completed surveys across two semesters and provided communication data used to reconstruct their social networks. Methods: Subjective perceptions of loneliness are measured…

The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An understanding of student profiles, such as who they are and how they behave, is critical to improving personalized support of MOOC learning environments. While past studies have explored different types of…

This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…

Education is constantly evolving as a field that shapes the future of societies, so identifying the key topics and prominent studies of educational research in 2023 will help move in the right direction. This study aims to identify the most important and current topics in the field of education through a bibliometric analysis of articles published…