Data collection and analyzation practices for English language development services are scarcely found in research, but needed in the subgroup of minority students commonly known as English language learners (Wiseman & Bell, 2021). Wiseman and Bell (2021) identified ELLs as one of the most under-documented student subgroups in the American…

Quality, timely, purpose-driven education in emergencies (EiE) data can enable more effective response to education needs in crisis settings and strengthen system resilience. However, a growing body of evidence points to a number of problems related to the production, sharing, and use of EiE data within education information management systems…

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…

The purpose of the DaSy Data System Framework (referred to as DaSy framework) is to assist Part C (Early Intervention) and Part B (School-Aged) 619 programs in developing and enhancing high-quality state data systems for the collection, analysis, reporting, and use of their Individuals with Disabilities Education Act (IDEA) data. The DaSy…

With the development of the information age, the quality of physical education teaching in universities has become an important goal of teaching reform. Improving the quality of physical education and significantly improving students' physical fitness is one of the development goals of higher education. Therefore, this article proposes an…

Sustainable quality education is a big challenge even for the developed countries. In response to this, education 4.0 is gradually expanding as a new era of education. This work intends to unfold some hidden parameters that are affecting the quality education ecosystem (QEE). Academic loafing, unawareness, non-participation, dissatisfaction, and…

"Using Data for Continuous Improvement in Educator Preparation" provides case studies that illuminate and contextualize the ways in which educator preparation programs determine the data they need to improve, collect data, analyze data, share data with stakeholders, and close the loop by making focused improvements based on the data.…

To analyze educational outcomes or evaluate operations, academic institutions need to produce high-quality data. Unfortunately, many institutions do not have accurate, timely, and useful data and information despite investments to manage technology. Furthermore, data management issues in education, including access, quality, and ownership, inhibit…

Our primary objective in this Special Issue was to respond to potential criticisms of AIED in potentially "perpetuating poor pedagogic practices, datafication, and introducing classroom surveillance" and to comment on the future of AIED in its coming of age. My overarching assumption in response to this line of critiques is that humans…

The presented work is a student marks and grade prediction system using supervised machine learning techniques, the system is developed on the historic performance of students. The data used in this research is collected from Federal Board of Intermediate and Secondary Education Islamabad Pakistan, there are 7 regions in FBISE i.e. Punjab, Sindh,…

Early childhood is a crucial stage in a child's life, and aspects of the environment in the physical, social-emotional, cognitive, and health and safety domains all play important roles in shaping children's development during these early years. Having a valid and reliable measure of the quality of these aspects of children's care settings is…

The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…

Higher education (HE) is a challenging area for quality professionals because of its highly complex operational nature. While neither quality management (QM) in HE nor applications of analytics in QM is a new research discipline, few studies have examined the applications of analytics in the context of QM in HE. This study calls for more attention…

The purpose of this review is to examine the current literature on incremental rehearsal (IR) to investigate whether IR is be considered an evidence-based practice, based on the quality indicators set forth by the Council for Exceptional Children (Cook et al., 2014). Burns et al. (2012) completed a meta-analysis to investigate the effectiveness…

The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…