Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…

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…

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…

Purpose: In light of a need for more critical education about datafication, this paper aims to develop a framework for critical datafication literacy that is grounded in theoretical and empirical research. The framework draws upon existing critical data literacies, an in-depth analysis of three well-established educational approaches - media…

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…

This study focuses on Grounded Theory, which is one of the qualitative research designs. Glaser and Strauss developed the Grounded Theory; it has been revised by other scientists, resulting in three distinct Grounded Theory approaches: the systematic design (Corbin and Strauss approach), the classical design (Glaser approach), and the…

This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…

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…

In modeling missing data, the missing data latent variable of the confirmatory factor model accounts for systematic variation associated with missing data so that replacement of what is missing is not required. This study aimed at extending the modeling missing data approach to tetrachoric correlations as input and at exploring the consequences of…

Purpose: The unanticipated changes in state legislation in Idaho, Indiana, Michigan, Tennessee, and Wisconsin in 2011-12 significantly restricted or entirely prohibited the collective bargaining rights of teachers. Considering these institutional changes as a natural experiment, we examine the causal impact of weakening teacher unionization on…

As California invests in early learning and care, the state is also moving forward with a long-overdue plan to build a statewide longitudinal data system (SLDS) -- known as the Cradle-to-Career (C2C) Data System -- which will eventually connect data over time and across sectors like education, health, human services, and the workforce. This is a…

Quantitative evidence synthesis methods aim to combine data from multiple medical trials to infer relative effects of different interventions. A challenge arises when trials report continuous outcomes on different measurement scales. To include all evidence in one coherent analysis, we require methods to "map" the outcomes onto a single…

Each year, state legislators introduce hundreds of bills that generate new data collections, analyses, and resources, playing a crucial role in how people access and use data. Notably, in 2023 legislators introduced and enacted bills governing cross-agency data systems--the most important step that states must take to make robust access to data…

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…

Conducting high-quality overviews of reviews (OoR) is time-consuming. Because the quality of systematic reviews (SRs) varies, it is necessary to critically appraise SRs when conducting an OoR. A well-established appraisal tool is A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2, which takes about 15-32 min per application. To save time,…