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Blackmon, Stephanie J. – Change: The Magazine of Higher Learning, 2023
Student privacy is a critical area of higher education that deserves greater focus, particularly as student data digitalization increases. Many colleges and universities use data literacy as a way to prepare students, sometimes from different disciplines, to work with others' data postgraduation. Data literacy can be an avenue for helping all…
Descriptors: Privacy, Data Collection, Data Use, Higher Education
Chinsook, Kittipong; Khajonmote, Withamon; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jantakoon, Thada – Higher Education Studies, 2022
Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…
Descriptors: Student Behavior, Learning Analytics, Computer Software, Rating Scales
Miguel, Hugo Gonzaga; Ramos, Pedro; da Cruz Martins, Susana; Costa, Joana Martinho – Education for Information, 2020
One of the most widely researched issue on higher education relates to exposed paths that lead to academic success. Nowadays information systems represent an essential part of the education sector in many universities. In particular, the increasing of the number of students in higher education in Portugal leads to the progressive increase of…
Descriptors: Foreign Countries, Educational Research, Higher Education, Academic Achievement
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
Sarah E. Long – ProQuest LLC, 2021
Missing values that fail to be appropriately accounted for may lead to reduced statistical power, biased estimators, reduced representativeness of the sample, and incorrect interpretations and conclusions (Gorelick, 2006). The current study provided an ontological perspective of data manipulation by explaining how statistical results can…
Descriptors: Statistics, Data Use, Student Records, School Holding Power
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
Cynthia N. Carvajal; Felecia Russell; Yadira Ortiz – Association for Institutional Research, 2024
Inclusivity in data reports for undocumented students can be difficult to achieve. By nature of those students' status and livelihood, there is contention among academics and practitioners on whether this is a population that should not be formally tracked or identified, for a variety of reasons. Concerns about tracking arise because of the…
Descriptors: Inclusion, Undocumented Immigrants, Critical Theory, Privacy
Nowicki, Ewa – College and University, 2019
Current college-aged students, broadly referred to in this article as Gen Z, are entering adulthood with the concept of gender as a spectrum rather than a binary. However, student information systems (SISs) in use throughout U.S. higher education institutions were built with retention and collection practices relative to binary sex and identity…
Descriptors: Success, Higher Education, College Students, Best Practices
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
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
Prinsloo, Paul – E-Learning and Digital Media, 2017
In the socio-technical imaginary of higher education, algorithmic decision-making offers huge potential, but we also cannot deny the risks and ethical concerns. In fleeing from Frankenstein's monster, there is a real possibility that we will meet Kafka on our path, and not find our way out of the maze of ethical considerations in the nexus between…
Descriptors: Mathematics, Decision Making, Higher Education, Data Collection
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
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
Reidenberg, Joel R.; Schaub, Florian – Theory and Research in Education, 2018
Education, Big Data, and student privacy are a combustible mix. The improvement of education and the protection of student privacy are key societal values. Big Data and Learning Analytics offer the promise of unlocking insights to improving education through large-scale empirical analysis of data generated from student information and student…
Descriptors: Data Collection, Information Security, Student Records, Privacy
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