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Denisa Gándara; Rosa Maria Acevedo; Diana Cervantes; Marco Antonio Quiroz; Isabel McMullen; Tarini Kumar – Innovative Higher Education, 2025
Substantial shares of eligible students forgo or lose access to tuition-free college benefits, in part due to limited access to information on eligibility and other requirements. Given students' dependence on the Internet for information on how to pay for college, we examine the availability and digital accessibility of critical program…
Descriptors: Tuition, Eligibility, State Programs, Costs
Jenay Robert; Kathe Pelletier; Betsy Tippens Reinitz – Strategic Enrollment Management Quarterly, 2024
In today's digital world, higher education institutions collect and use more data than ever. However, institutional silos create barriers for stakeholders who need data for daily operations and strategy. This article presents a vision of a unified, collaborative future for data governance and actionable steps stakeholders can take.
Descriptors: Data Analysis, Data Collection, Information Management, Governance
Yun Du – International Journal of Web-Based Learning and Teaching Technologies, 2024
This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…
Descriptors: Educational Innovation, Preschool Education, Data Analysis, Data Collection
Nurten Gündüz; Mehmet Sincar – Problems of Education in the 21st Century, 2025
Without regulations for higher education institutions in the metaverse, ethical transgressions are unavoidable. Educational metaverse systems, which integrate artificial intelligence, essentially depend on big data as their core technology, leading to considerable privacy issues. Therefore, this study examines data privacy and security issues, a…
Descriptors: Higher Education, Information Security, Privacy, Artificial Intelligence
Alexandra M. Pierce; Melissa A. Collier-Meek; Thea R. Bucherbeam; Lisa M. H. Sanetti – Communique, 2024
Students cannot experience the full potential benefits of an intervention unless they are receiving the intervention. This is the second installment in a three-part series on intervention fidelity designed to highlight the importance of ensuring classroom supports are implemented as intended. This article provides guidance related to measuring and…
Descriptors: Data Use, Decision Making, Intervention, Fidelity
Schildkamp, Kim; Datnow, Amanda – Leadership and Policy in Schools, 2022
Because learning from failures is just as important as learning from successes, we used qualitative case study data gathered in the Netherlands and the United States to examine instances in which data teams struggle to contribute to school improvement. Similar factors in both the Dutch and U.S. case hindered the work of the data teams, such as…
Descriptors: Foreign Countries, Educational Improvement, Data Use, Failure
Zeynab (Artemis) Mohseni; Italo Masiello; Rafael M. Martins – Education and Information Technologies, 2024
There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…
Descriptors: Elementary School Students, Data, Individual Development, Learning Trajectories
Liang Zhang; Jionghao Lin; John Sabatini; Conrad Borchers; Daniel Weitekamp; Meng Cao; John Hollander; Xiangen Hu; Arthur C. Graesser – IEEE Transactions on Learning Technologies, 2025
Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…
Descriptors: Artificial Intelligence, Academic Achievement, Data, Evaluation Methods
Petya Ilieva-Trichkova; Pepka Boyadjieva; Ralitsa Dimitrova – European Journal of Higher Education, 2024
In the context of higher education's growing significance and the persistence of inequalities in it, the article aims to further develop the understanding of higher education as a public good and to explore its association with social cohesion in a European comparative perspective. It shifts the focus from the content of higher education as a…
Descriptors: Foreign Countries, Prosocial Behavior, Higher Education, Equal Education
Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
Katherine Bui; Keith R. Berry Jr. – Journal of Research Administration, 2025
Research administrators (RA) at institutions of higher education (IHE) provide critical support to faculty throughout the lifecycle of research, which include developing research, applying to funding opportunities, managing awards through closeout, and maintaining compliance. Fulfilling these tasks requires well-developed RA processes and clear…
Descriptors: COVID-19, Pandemics, Data Collection, Data Use
Caspari-Sadeghi, Sima – Journal of Educational Technology Systems, 2023
Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…
Descriptors: Artificial Intelligence, Educational Technology, Computer Assisted Testing, Barriers
Michael Yao Wodui Serwornoo; Samuel Danso; Benedine Azanu; Eric Opoku-Mensah – Journalism and Mass Communication Educator, 2024
The digital era has significantly reshaped journalism, emphasizing the pivotal role of data-driven reporting. This review delves into the nexus of data journalism and journalism education, investigating dominant study characteristics, challenges, and gaps for future research. Examining 41 relevant articles through the Arksey and O'Malley…
Descriptors: Journalism Education, Data Analysis, Journalism, Decision Making
Luke Billingham; Fern Gillon – British Educational Research Journal, 2024
School exclusion reduction in Scotland--and especially in the city of Glasgow--has received substantial media and policy attention in recent years. In London in particular, multiple governmental agencies have explicitly expressed a desire to replicate the exclusion reduction which recently occurred in Glasgow, often citing the connection between…
Descriptors: Foreign Countries, Expulsion, Barriers, Incidence
Ferdinand Valentin Stoye; Claudia Tschammler; Oliver Kuss; Annika Hoyer – Research Synthesis Methods, 2024
The development of new statistical models for the meta-analysis of diagnostic test accuracy studies is still an ongoing field of research, especially with respect to summary receiver operating characteristic (ROC) curves. In the recently published updated version of the "Cochrane Handbook for Systematic Reviews of Diagnostic Test…
Descriptors: Diagnostic Tests, Accuracy, Barriers, Models

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