Big Data offers opportunities and challenges in all aspects of human life. In relation to research ethics, Big Data represents a normative difference in degree rather than a difference in kind. Data are more messy, rapid, difficult to predict, and difficult to identify owners; but the principles of informed consent, confidentiality, and prevention…

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…

A major pre-award administrative challenge research universities face is turnaround time for generation of high-quality NIH Data Training Tables for NIH training grants (e.g., T32, K12, TL1, KL2, R25s) which are required for training grant submission proposals to the National Institutes of Health (NIH). Universities with dedicated training grant…

In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…

This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…

As part of a study investigating research productivity of sociology PhD students in Australia, an application to the federal government's Department of Education, Skills and Employment (DESE) aimed to establish a baseline count of completed sociology doctorates by university. It was anticipated that university totals might be different from PhD…

The Grand Challenges for Assessment in Higher Education project is a collaborative effort of 10 endorsing organizations and over 400 volunteers to increase the extent to which assessment (1) supports equity; (2) is visible, actionable, and drives innovation; and (3) guides rapid improvements in pedagogy (Singer-Freeman and Robinson 2020). Several…

Historic data in analog (or print) format is a valuable resource that is utilized by scientists in many fields. This type of data may be found in various locations on university campuses including offices, labs, storage facilities, and archives. This study investigates whether biological data held in one institutional university archives could be…

This dissertation address two significant challenges in the causal inference workflow for Big Observational Data. The first is designing Big Observational Data with high-dimensional and heterogeneous covariates. The second is performing uncertainty quantification for estimates of causal estimands that are obtained from the application of black box…

This study conducted a systematic literature review of articles on learning analytics published between 2004 and January 2024. A total of 1,064 articles, identified using the keyword "learning analytic*" in the Scopus database, were analyzed. The study integrated systematic literature review and bibliometric analysis approaches to…

This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…

Speculative reform jumps the gun on notions of data-driven reform, requiring administrators to anticipate and act to ensure problems (and the data that would show them) do not materialize. Speculative reforms are incapable of delivering the outcomes they promise, as they are fueled by a fear of the future that their reforms do not extinguish. In…

With Open Data becoming more popular and more public bodies publishing their datasets, the need for educating prospective graduates on how they can use them has become prominent. This study examines the use of the Problem Based Learning (PBL) method and educational technologies to support the development of Open Data skills in university students.…

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…

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,…