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Showing 1 to 15 of 42 results Save | Export
Isaac, James; Velez, Erin; Roberson, Amanda Janice – Institute for Higher Education Policy, 2023
Students, families, colleges, and lawmakers need clearer information on postsecondary outcomes to make informed decisions. By leveraging data available at institutions and federal agencies, a nationwide student-level data network (SLDN) would close information gaps that persist in our higher education landscape to answer critical questions about…
Descriptors: College Students, Data, Information Networks, Program Design
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
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Motz, Benjamin; Busey, Thomas; Rickert, Martin; Landy, David – International Educational Data Mining Society, 2018
Analyses of student data in post-secondary education should be sensitive to the fact that there are many different topics of study. These different areas will interest different kinds of students, and entail different experiences and learning activities. However, it can be challenging to identify the distinct academic themes that students might…
Descriptors: Data Collection, Data Analysis, Enrollment, Higher Education
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Pratsri, Sajeewan; Nilsook, Prachyanun – Higher Education Studies, 2020
According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the…
Descriptors: Data Analysis, Higher Education, Information Systems, Data Collection
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Marachi, Roxana; Quill, Lawrence – Teaching in Higher Education, 2020
The Canvas Learning Management System (LMS) is used in thousands of universities across the United States and internationally, with a strong and growing presence in K-12 and higher education markets. Analyzing the development of the Canvas LMS, we examine 1) 'frictionless' data transitions that bridge K12, higher education, and workforce data 2)…
Descriptors: Management Systems, Longitudinal Studies, Data Analysis, Higher Education
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Williamson, Ben – British Journal of Educational Technology, 2019
Digital data are transforming higher education (HE) to be more student-focused and metrics-centred. In the UK, capturing detailed data about students has become a government priority, with an emphasis on using student data to measure, compare and assess university performance. The purpose of this paper is to examine the governmental and commercial…
Descriptors: Foreign Countries, Higher Education, Technology Uses in Education, Data Analysis
Christina Ciocca Eller – Annenberg Institute for School Reform at Brown University, 2019
The rise of accountability standards has pressed higher education organizations to oversee the production and publication of data on student outcomes more closely than in the past. However, the most common measure of student outcomes, average bachelor's degree completion rates, potentially provides little information about the direct impacts of…
Descriptors: Higher Education, Accountability, Graduation Rate, Bachelors Degrees
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Jones, Kyle M. L.; McCoy, Chase – Learning, Media and Technology, 2019
In this article, we argue that the contributions of documentation studies can provide a useful framework for analyzing the datafication of students due to emerging learning analytics (LA) practices. Specifically, the concepts of individuals being 'made into' data and how that data is 'considered as' can help to frame vital questions concerning the…
Descriptors: Data Analysis, Documentation, Guidelines, Data Collection
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Green, Paula; Baumal, Brian – College Quarterly, 2019
Legal, privacy and ethical concerns impacted data sharing among post-secondary institutions in academic collaboration in Ontario. The legal/ethical environment was embodied by FIPPA (Freedom of Information and Protection of Privacy) legislation, Research Ethics Board protocols and Institutional Acts enacted by the provincial parliament.…
Descriptors: Privacy, Ethics, Legal Problems, Classification
Perry, Chantel A. – Online Submission, 2018
This study aims to develop a list of technological enhancements to a financial aid analytics application (F3A) designed to assist higher education leaders in gaining actionable insights for decision-making with grants optimization. This research utilizes the Design Science Research framework which highlights the design and evaluation of an IT…
Descriptors: Computer Software, Student Financial Aid, Data Analysis, Higher Education
Campaign for College Opportunity, 2019
With over 37 million residents, California is the most populous state in the country. California's primary and secondary schools enroll over 6.2 million students,1 and there are 3.4 million undergraduates attending 683 postsecondary institutions in California. Yet, because of the lack of a strong data infrastructure, we are unable to answer basic…
Descriptors: Data Collection, Data Analysis, Higher Education, Access to Education
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Henry, Philip – College and University, 2019
Phillip Henry is a semi-retired former U.K. Registrar and Secretary with almost 40 years' experience in higher education. He has been active in staff development in the United Kingdom (Association of University Administrators, Academic Registrars Council, and Association of Heads of University Administration), in the United States (AACRAO and a…
Descriptors: Academic Achievement, Administrator Attitudes, Educational Experience, College Students
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Prinsloo, Paul; Slade, Sharon – Journal of Learning Analytics, 2016
In light of increasing concerns about surveillance, higher education institutions (HEIs) cannot afford a simple paternalistic approach to student data. Very few HEIs have regulatory frameworks in place and/or share information with students regarding the scope of data that may be collected, analyzed, used, and shared. It is clear from literature…
Descriptors: Data Collection, Data Analysis, Educational Research, Information Security
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Raju, Dheeraj; Schumacker, Randall – Journal of College Student Retention: Research, Theory & Practice, 2015
The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…
Descriptors: Student Characteristics, Higher Education, Graduation Rate, Academic Persistence
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de Freitas, Sara; Gibson, David; Du Plessis, Coert; Halloran, Pat; Williams, Ed; Ambrose, Matt; Dunwell, Ian; Arnab, Sylvester – British Journal of Educational Technology, 2015
With digitisation and the rise of e-learning have come a range of computational tools and approaches that have allowed educators to better support the learners' experience in schools, colleges and universities. The move away from traditional paper-based course materials, registration, admissions and support services to the mobile, always-on and…
Descriptors: Higher Education, Student Records, Data Analysis, Information Utilization
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