Missing data in scientific research go hand in hand with assumptions about the nature of the missingness. When dealing with missing values, a set of beliefs has to be formulated about the extent to which the observed data may also hold for the missing parts of the data. It is vital that the validity of these missingness assumptions is verified,…

Professionals working with individuals at risk for, or with, disabilities are required by federal legislation to select, implement, and formatively and summatively evaluate the effectiveness of evidence-based practices in typical settings. Although multiple resources related to graph construction and visual analysis are available in the…

Many research agencies are now requiring that data collected as part of funded projects be shared. However, the practice of data sharing in education sciences has lagged these funder requirements. We assert that this is likely because researchers generally have not been made aware of these requirements and of the benefits of data sharing.…

Strategy and research are essential parts of strategic enrollment management (SEM), yet little information exists regarding how to use research and predictive analytics for effective strategy. It is often easier to react to what is happening in the moment, rather than be proactive in predicting the future or developing long-term plans. This…

Manually determining concepts present in a group of questions is a challenging and time-consuming process. However, the process is an essential step while modeling a virtual learning environment since a mapping between concepts and questions using mastery level assessment and recommendation engines is required. In this article, we investigated…

Researchers frequently use Rasch models to analyze survey responses because these models provide accurate parameter estimates for items and examinees when there are missing data. However, researchers have not fully considered how missing data affect the accuracy of dimensionality assessment in Rasch analyses such as principal components analysis…

In this chapter, we draw on the data collected during our evaluations of six TAACCCT grants to describe the challenges, successes, and transformative effect of adopting a developmental evaluation approach for community college programs.

The growth of multimedia and increasing archival of this footage by public safety agencies presents as a watershed moment in converting this footage into actionable data that can inform and improve public safety practice. However, despite the considerable volume of archival footage, there remains a profound lack of research leveraging this data.…

In recent years, modern technologies have enabled the collection of exponentially larger quantities of data in the biomedical domain and elsewhere. In particular, the advent of single-cell genomics has allowed for the collection of datasets containing hundreds of thousands of cells measured in tens of thousands of dimensions. This rapid expansion…

Although the use of real-world data sets is encouraged when teaching statistics, it can be difficult for instructors to find meaningful data for introducing students to univariate descriptive statistics such as the mean, median, and percentiles. The recent lead contamination of the water supply in Flint, Michigan, provides a real-life data set…

In this chapter, we review the strengths of NCES survey data, provide an example of analyzing NCES survey data to explore the pathways between coursework in career and technical education in high school and postsecondary success, and offer suggestions for future data collection.

Artificial intelligence and data analysis (AIDA) are increasingly entering the field of education. Within this context, the subfield of learning analytics (LA) has, since its inception, had a strong emphasis upon ethics, with numerous checklists and frameworks proposed to ensure that student privacy is respected and potential harms avoided. Here,…

Multiple perspective interviews (MPIs) involve interviewing members of a social group separately and triangulating their accounts during analysis to gain insights into the functioning of such groups (e.g. families). So far, there has been little engagement with the specific challenges of MPI research during the analysis, particularly with…

In this project, students asked and attempted to answer questions about themselves by collecting and analyzing data. With the prevalence of big data and business analytics, managers have data and quantitative information available more immediately than ever. However, managers need to understand how to use this information. In this project,…

Data sprints have emerged as a popular way to involve stakeholders in datawork. In this chapter we discuss what it takes to turn a sprint into a productive situation of inquiry (in the sense of Dewey, 1938). We argue that sprint organizers must work actively to counteract an otherwise docile setting where the preference for agreement between…