Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…

This systematic literature review critically evaluates 14 empirical studies published over a 14 years span (2006-2019) to answer questions about the models and the effects of transformational school leadership on student academic achievement. The analysis of the related literature utilized vote counting and narrative synthesis to delineate the…

This paper explores using data mining in English teaching assessment in higher education within the 'Internet + Education' era. Traditional assessment methods struggle to meet modern teaching needs. By collecting diverse data like student performance and learning behavior, and employing data mining, a comprehensive assessment model is built. This…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

Education Savings Accounts (ESAs) are government-funded accounts typically established for parents who opt not to enroll their children in public kindergarten through grade 12 (K--12) schools. ESAs allow parents to spend funds that the state would have spent for their student to attend their local public school on a broad array of educational…

The Data Culture Framework is a high-level guide designed for institutional leaders who want to create and sustain an effective data culture on campus. The Framework offers a set of practices designed to help institutions of higher education create and maintain an effective data-informed community among institutional leaders, faculty, and staff.

Schooling in Australia has become subject to increased processes of data-based governance. This article draws upon the insights of an experienced teacher, 'Meriam', who, having taught more than 34-years over almost a 50-year span, reflected upon the nature of such changes. Utilising theorising in relation to datafication processes and…

Administrative data are increasingly being used to study inequalities in education. Yet a well-known difficulty with such resources is the limited information they hold. A commonly used proxy for children coming from a low-income background is their eligibility for free school meals, yet this is likely to be of little use in measuring academic…

This study aimed to extend previous literature comparing continuous methods of data collection to estimation data, but this time implementing the data collection procedures within a group discrete trial teaching format with three individuals diagnosed with autism spectrum disorder. Group discrete trial teaching was conducted in a classroom setting…

In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…

The purpose of this study was to provide initial evidence of the effectiveness of Check-In/Check-Out-High School (CICO-HS) on high school student outcomes. Check-In/Check-Out-High School is a version of CICO, an established Tier 2 intervention designed to improve student academic and social behavior, adapted to increase effectiveness and…

Inclusivity in data reports for undocumented students can be difficult to achieve. By nature of those students' status and livelihood, there is contention among academics and practitioners on whether this is a population that should not be formally tracked or identified, for a variety of reasons. Concerns about tracking arise because of the…