Purpose: This study aims to analyze the platforming scenario at a Brazilian university as well as the data security process for students and professors. Design/methodology/approach: This research brings an analysis through a qualitative approach of the platformization process in a Brazilian teaching institution. Findings: The results point to a…

In this review, I examined the last two decades of research on data use in education to outline the ways in which principals used data to inform their own leadership practices. I found three themes: first, student achievement data were the most widespread form of data that principals used; second, principals' work has been reshaped by teacher…

Purpose: This study aims to explore the perception of algorithm accuracy among data professionals in higher education. Design/methodology/approach: Social justice theory guided the qualitative descriptive study and emphasized four principles: access, participation, equity and human rights. Data collection included eight online open-ended…

Schools and school districts use social media for a variety of reasons, but alongside the benefits of schools' social media use come potential risks to students' privacy. Using a novel dataset of around 18 million Facebook posts by schools and districts in the United States, we explore the extent to which personally identifiable information of…

Purpose: Building on past studies of library privacy policies, this review looks at how privacy information is shared at universities and colleges in the state of Florida. Beyond the question of whether a library-specific privacy policy exists, this review evaluates what is covered in the policies -- whether topics such as how student data is…

Contribution: This work provides evidence of various approaches to studying longitudinal student unit record data in undergraduate education in the USA and the outcomes that can be realized using a large multi-institutional longitudinal dataset, Multiple-Institution Database for Investigating Longitudinal Development (MIDFIELD). Background:…

Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…

Safeguarding personal digital data is crucial and requires appropriate training. However, privacy remains a novel topic, leaving teachers with limited guidance. This study investigates how elementary school students perceive personal data and assesses pre-service teachers' accuracy in predicting children's responses. Employing Nissenbaum's…

This study employed a qualitative research design to investigate the utilization of soft pedagogical documents among twelve mathematics teachers in five purposively sampled public secondary schools. Data was collected through interviews and analyzed thematically. The study, rooted in social constructivism theory, discovered a mixed pattern in the…

Educational data mining has allowed for large improvements in educational outcomes and understanding of educational processes. However, there remains a constant tension between educational data mining advances and protecting student privacy while using educational datasets. Publicly available datasets have facilitated numerous research projects…

Objective: The purpose of this study was to establish the response rate of first-time college students to a vaccination records request, and to obtain student vaccination rates for selected vaccines. Participants: Student health records for the fall 2018 cohort of first-time college students were reviewed. Methods: Vaccination and response rates…

Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…

This study focuses on the analysis of school exclusion, which underlies and causes early school leaving, in 20 schools around Porto, Portugal. It is based on the qualitative and documental study of the personal school files of 25 youth, born between 1996 and 2003, who have left school and are now in a situation of social exclusion. We created a…

Research using school discipline and infraction data has contributed to public policy conversations by helping elucidate the effects of and disproportionate experience of school disciplinary outcomes. This research brief presents results from an analysis of the public availability of such data from state departments of education. Findings suggest…

Since 2010, the State Higher Education Executive Officers Association's (SHEEO) Strong Foundations survey has reported on the evolution and value of postsecondary student unit record systems (PSURSs) by illuminating the condition of state postsecondary data in the U.S. In the "Strong Foundations 2023" survey, which was administered from…