Data showing what students earn after attending higher education institutions have become increasingly available, bolstering calls from policymakers and advocates that government financial aid programs should be tied to those outcomes. Often overlooked, however, is that these data and policies usually reflect the earnings of only students who…

The use of group work projects is common in introductory statistics courses, including projects where students collect their own data. However, the COVID-induced lockdown at the start of 2020 meant that data collection was compromised. In this study, we examine a situation where students were permitted to use artificial (made-up) data for their…

This report examines how states can use their Statewide Longitudinal Data Systems (SLDS) to better understand their teacher supply problems and assess initiatives designed to address them. It emphasizes two key actions: connecting existing data and collecting new data on the prospective workforce. Using research and real-world examples from four…

In 2024, state legislators introduced hundreds of bills that would affect data collection, access, and use across early education, K-12, postsecondary, and the workforce. As in 2023, legislators continued to introduce and enact legislation governing cross-agency data systems. These policies are the most important step toward making statewide…

This essay provides a two-pronged critical assessment of a subset of the literature on racial disproportionality in special education: that which aims to estimate racial disparities among otherwise similar children. This body of research has shown that Black students are less likely than "comparable" White students to receive special…

Purpose: The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their…

U.S. colleges and universities are under increasing pressure to appear racially diverse, but have yet to account systematically for a quickly growing contingent of multiracial-identifying students. Drawing on interviews with multiracial-identifying undergraduates at Western University, I demonstrate how everyday university practices compromise…

Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…

Massive open online courses offer a valuable platform for efficient and flexible learning. They can improve teaching and learning effectiveness by enabling the evaluation of learning behaviors and the collection of feedback from students. The knowledge map approach constitutes a suitable tool for evaluating and presenting students' learning…

As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…

Businesses and other organizations across the globe are becoming more and more data-driven, using a combination of descriptive, diagnostic, predictive and prescriptive analytics to gain a strategic advantage through understanding the past, what we hope to happen in the future, and the ability to accurately predict future outcomes. These forms of…

Digital learning environments are becoming increasingly ubiquitous as a wide range of EdTech products and services enter classrooms and households across the globe. One salient attribute of these environments is their capacity to generate large amounts of data as students interact with the technology. These data logs can help construct a detailed…

Many departments seek to improve their equity, diversity, and inclusion using data-informed methods; however, not much is known about how closely department leadership aligns their review practices with appropriate theory. This dissertation seeks to explore four areas: 1) how are equity, diversity, and inclusion are being conceptualized (implied…

Across the international higher education sector, existing studies highlight that student evaluations of courses and teaching are biased and prejudiced towards academics and can cause mental distress. Yet student evaluation data is often used as part of faculty hiring, firing, promotion, award and grant decisions. That a data source known to be…

Data Analytics has grown dramatically in importance and in the level of business deployments in recent years. It is used across most functional areas and applications, some of the latter including market campaigns, detecting fraud, determining credit, identifying assembly line defects, health services and many others. Indeed, the realm of…