Principals at Hunter School District, a pseudonym, lacked capacity for using data, a reflection of the district's lack of a culture of data-driven decision-making. HSD was located in New York City, with 23 schools serving 11,600 students; students were 90% Black or Latino with 90% coming from low-income families and 20% living in temporary…

This study aimed to discover the perspectives and experiences of elementary school teachers in rural southeast Tennessee regarding their collaborative efforts to effectively implement data-driven instruction for individual student success. The research problem is that the current collaboration efforts for teachers to implement data-driven…

The Civil Rights Data Collection (CRDC) is a mandatory survey of all public schools and school districts in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico. Since the 2009-10 CRDC, schools and school districts have reported the number of students who were referred to law enforcement and arrested at the nation's public schools.…

The purpose of this study was to investigate the effectiveness of four different models (bifactor, CTC(M-1), CTCU and unidimensional) as to optimal model selection when the wording effect associated with negatively worded items was present. A Monte Carlo simulation study was conducted to compare model-data fit and accuracy in parameter estimates…

Over recent years, the sharing of personal data among students is uncontrolled, especially on the social media networks, resulting in widespread data intrusions that compromise their privacy and confidentiality. Against this backdrop, this study was conducted to identify the level of knowledge of personal data protection among students. This…

In this study, it was aimed to examine the effect of missing data in different patterns and sizes on test equating methods under the NEAT design for different factors. For this purpose, as part of this study, factors such as sample size, average difficulty level difference between the test forms, difference between the ability distribution,…

In order to produce the most reliable syntheses of the effectiveness of educational interventions, systematic reviews need to adhere to rigorous methodological standards. This meta-review investigated risk of bias occurring while conducting a systematic review and the presence of open science practices like data sharing and reproducibility of the…

Data mining (DM) is an in-depth approach to data analysis by mining useful information from large amounts of data, and this technique is now being used in an increasing number of fields. In this paper, the authors present the design of a real-time data analysis system for sports training based on DM technology and use the corresponding mining…

Background: Science education should encompass enculturation in science which implies performing scientific practices such as use of data and modelling, in authentic contexts like the field. Purpose: This work aims to determine how preservice elementary teachers (PETs) use data obtained in the field, and how these data contribute to the process of…

We use Eurobarometer data to examine barriers to international student mobility. Multivariate analysis is employed to study how individual characteristics are related to the obstacles preventing higher education students from participating in activities in another EU country. The results suggest that several demographic factors including area of…

The demand for a creative workforce has never been higher, yet schools struggle to teach and assess creativity among students efficiently. Compositions are an effective way to incorporate creativity across the curriculum; however, essays are time consuming to evaluate for quality or creativity. This study explored (a) if high creativity scores are…

Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…

Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…

The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to its devasting effects on students' academic development, the disruptions to schooling had important consequences for researchers conducting effectiveness studies on educational programs during this era. Given the likelihood of future large-scale disruptions, it is…

This study aimed to address the state of data driven decision practices within the Division of Student Affairs at South County College. Framed by an exploratory qualitative case study, this project conducted semi-structured interviews of directors of student affairs and a document analysis of annual reports of the seven departments that constitute…