As organizations' reliance on data increases, the prevalence of data analytics programs in universities likewise increases. However, despite this specialized education, scholars still report a gap between the knowledge and skills students graduate with and those required by industry upon beginning work as an entry-level data analyst. We draw on…

Latent change score (LCS) models are a powerful class of structural equation modeling that allows researchers to work with latent difference scores that minimize measurement error. LCS models define change as a function of prior status, which makes it well-suited for modeling developmental theories or processes. In LCS models, like other latent…

Opioid use is common among Social Security Disability Insurance (SSDI) beneficiaries, who account for a disproportionate share of opioid-related hospitalizations and mortality in the United States. However, little is known about the prevalence of opioid use prior to SSDI enrollment. Understanding when opioid use is established and how it…

This paper describes a short module for introducing data science to senior school students or other data-science beginners. The design focuses on "data moves." Students use CODAP to do their work.

The analysis of sequence data poses a great challenge; existing methods for the comparison of sequences take what theoretical grounding they have from other fields (most importantly, genetics). We argue that set theory provides a way of establishing the relations between sequences that has a natural application to the case in which the sequences…

Technologies and teaching practices can provide a rich log data, which enables learning analytics (LA) to bring new insights into the learning process for ultimately enhancing student success. This type of data has been used to discover student online learning patterns, relationships between online learning behaviors and assessment performance.…

Those asked to make valid decisions with data don't have the technical knowledge to understand nuance around data quality, assessment aims, and statistical limitations that influence how they should interpret the data. This reality is what Greg Thompson, Leslie Rutkowski, and David Rutkowski call the validity paradox. Educators can surmount this…

The Brazilian government has adopted measures that aim to influence students' spatial mobility. The extent and success of such measures require detailed knowledge of the mobility determinants. Gravity models are the appropriate tool for analyzing the flows of college students from their place of origin to their destination. To analyze the…

Most disability research is conducted in high-income countries, despite much of the world's population living in low- and middle-income countries. Given the flexible nature of qualitative research, studies using this methodology have the potential to provide important insights into how disability is perceived across the globe. The aim of the…

This volume is largely about nontraditional data; this paper is about a nontraditional visualization: classification trees. Using trees with data will be new to many students, so rather than beginning with a computer algorithm that produces optimal trees, we suggest that students first construct their own trees, one node at a time, to explore how…

Background: Many learners struggle to productively self-regulate their learning. To support the learners' self-regulated learning (SRL) and boost their achievement, it is essential to understand the cognitive and metacognitive processes that underlie SRL. To measure these processes, contemporary SRL researchers have largely utilized think aloud or…

Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…

For large-scale assessments, data are often collected with missing responses. Despite the wide use of item response theory (IRT) in many testing programs, however, the existing literature offers little insight into the effectiveness of various approaches to handling missing responses in the context of scale linking. Scale linking is commonly used…

Mixed methods research collects, analyzes, and integrates rigorous qualitative and quantitative methods to gain a deeper understanding of a phenomenon than would be gained by using either method alone. Integration is one of the key features of mixed methods research and consists of mixing qualitative and quantitative research in a systematic way…

Data from a moderately-selective state university in the Midwest is used to cross-examine the most appropriate data analytical techniques for predicting versus explaining college student persistence decisions. The current research provides an overview of the relative benefits of models specializing in prediction versus explanation with particular…