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Ford, Karly S.; Rosinger, Kelly; Choi, Junghee – Policy Futures in Education, 2022
Policy researchers have difficulty understanding stratification in enrollment in US higher education when race and ethnicity data are plagued by missing values. Students who decline to ethnoracially self-identify become part of a "race unknown" reporting category. In undergraduate enrollment, "race unknown" students are not…
Descriptors: Admission (School), Competitive Selection, Race, Ethnicity
Pretlow, Josh; Dunlop Velez, Erin; Roberson, Amanda Janice – Institute for Higher Education Policy, 2021
We cannot continue to ask students -- and their families -- to make one of the largest and most important investments of their lives without clearer information about what their time and money will yield. In partnership with RTI International (RTI), operating in an independent capacity, IHEP is gathering expert insights needed to support making…
Descriptors: College Students, Data, Information Networks, Federal Programs
Isaac, James; Pretlow, Josh; Cheng, Diane; Roberson, Amanda Janice – Institute for Higher Education Policy, 2022
We cannot continue to ask students -- and their families -- to make one of the largest and most important investments of their lives without clearer information about what their time and money will yield. Fortunately, support is broad across the country and across the political spectrum for a federal student-level data network (SLDN), which would…
Descriptors: College Students, Information Networks, Federal Programs, Higher Education
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Perez-Vergara, Kelly – Strategic Enrollment Management Quarterly, 2020
Institutional staff such as enrollment managers, business officers, and institutional researchers are often asked to predict enrollments. Developing any predictive model can be intimidating, particularly when there is no textbook to follow. This paper provides a practical framework for generating enrollment projection options and for evaluating…
Descriptors: Enrollment Projections, Enrollment Management, Enrollment Trends, Models
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So, Joseph Chi-ho; Wong, Adam Ka-lok; Tsang, Kia Ho-yin; Chan, Ada Pui-ling; Wong, Simon Chi-wang; Chan, Henry C. B. – Journal of Technology and Science Education, 2023
The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic…
Descriptors: Pattern Recognition, Artificial Intelligence, Higher Education, College Students
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Madsen, Miriam – Journal of Education Policy, 2021
The increased use of quantitative education data is often regarded by scholars as evidence of the emergence of 'governing by numbers'. These scholars ascribe major stakeholders such as the OECD and nation states agency as they produce, distribute and consume data, and respond to these with policy and management initiatives. This paper argues that…
Descriptors: Measurement, Evaluation Methods, Qualitative Research, Data Analysis
Fladd, Laurie; Heacock, Laurie; Hill-Kelley, Jennifer; Lawton, Julia; Pechac, Sharmaine; Shamah, Devora; Woodruff, Amber – Achieving the Dream, 2021
This guidebook is designed for institutional leaders and student success teams who are ready to talk openly about the students they serve and who are eager to learn practical strategies from national experts and peer institutions. We cannot design an experience that meets our students where they are unless we holistically understand who they are.…
Descriptors: Instructional Leadership, Instructional Design, Holistic Approach, Higher Education
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Rogaten, Jekaterina; Rienties, Bart Carlo – Higher Education Pedagogies, 2018
With the introduction of the Teaching Excellence Framework a lot of attention is focussed on measuring learning gains. A vast body of research has found that individual student characteristics influence academic progression over time. This case-study aims to explore how advanced statistical techniques in combination with Big Data can be used to…
Descriptors: STEM Education, Data Collection, 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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Bryan, Michael; Cooney, Darryl; Elliott, Barbara – National Center for Education Statistics, 2019
The 2012/17 Beginning Postsecondary Students Longitudinal Study (BPS:12/17), conducted by the National Center for Education Statistics (NCES) at the U.S. Department of Education, is the second follow-up of students who began postsecondary education in the 2011-12 academic year. BPS:12/17 draws from the 2011-12 National Postsecondary Student Aid…
Descriptors: Longitudinal Studies, Postsecondary Education, Student Financial Aid, School Statistics
Delisle, Jason D., Ed. – American Enterprise Institute, 2022
A long overdue, much needed transformation is underway in the higher education system. It started a decade ago, when federal and state policy­makers first began to collect data on what students earn after pursuing a postsecondary education. But new data are fundamentally differ­ent. Unlike broad-based national statistics, such as how much someone…
Descriptors: Higher Education, Educational Policy, Outcomes of Education, Income
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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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Baum, Sandy; Cunningham, Alisa; Tanenbaum, Courtney – Change: The Magazine of Higher Learning, 2015
The level of educational attainment in the United States is a central focus of public policy. The Obama administration, some states, large national foundations, and other organizations have set near-term goals to increase the number of Americans with college degrees. Achieving these goals is likely to involve a combination of increasing…
Descriptors: Educational Attainment, Higher Education, Educational Policy, Goal Orientation
Niemi, David; Gitin, Elena – International Association for Development of the Information Society, 2012
An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…
Descriptors: Higher Education, Online Courses, Academic Persistence, Identification
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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