Measurement systems give colleges a structure for collecting, sharing, and acting on data. The guidebook and tools presented here help faculty, staff, college leadership, and policymakers understand and use measurement systems--and specifically use data to improve completion rates, close institutional performance gaps, and facilitate economic…

Is public engagement with science deliberative and evidence-based? The public is often perceived as underprepared to use data and susceptible to partisan and emotional manipulation. Consequently, educational efforts focus on the ability to identify reliable information. We posit that effective engagement with science goes beyond this and hinges on…

The study explored the social perceptions of young children's use of smart devices in South Korea using big data methodologies. Big data methodologies allowed to uncover underlying thoughts and feelings about young children's use of smart devices that had not been discovered in existing studies. The study extracted raw data from three different…

Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…

The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the…

Single-case design (SCD) is frequently utilized in applied contexts, such as schools or clinics, due to its utility in evaluating individual intervention effects of students. Data collected in SCD are often displayed in a linear graph, which can vary drastically in their construction leading to inconsistencies in rater interpretation. This has led…

Dependability (also known as consistency) is one of four criteria in rigor and trustworthiness in qualitative research. In this article, the process of establishing consistency is discussed through the lenses of constructivism and interpretivism, as the observed social reality is viewed as epistemologically counter-intuitive. Two strategies were…

With three school years touched by the pandemic so far, the extent of the damage to this generation of students is coming into focus. Three concerns are top of mind for state and district leaders: making up for disrupted learning, ensuring that schools have enough quality teachers and staff to lead this work, and building a diverse teacher…

Predictive modeling is a core technique used in tackling various tasks in learning analytics research, e.g., classifying educational forum posts, predicting learning performance, and identifying at-risk students. When applying a predictive model, it is often treated as the first priority to improve its prediction accuracy as much as possible.…

Despite calls to increase the focus on explainability and interpretability in EDM and, in particular, student success prediction, so that it becomes useful for personalized intervention systems, only few efforts have been undertaken in that direction so far. In this paper, we argue that this is mainly due to the limitations of current Explainable…

A critical issue in using fine-grained gameplay data to measure learning processes is the development of indicators and the algorithms used to derive such indicators. Successful development--that is, developing traceable, interpretable, and sensitive-to-learning indicators--requires understanding the underlying theory, how the theory is…

Curriculum-based measurement (CBM) represents a critical strategy for data-based decisionmaking within educational settings. Visual analysis is frequently used to analyze CBM data; thus, CBM vendors often automatically generate graphs based on student data to facilitate analysis. Differences in graph formatting are apparent across CBM vendors, and…

In visual communication, people glean insights about patterns of data by observing visual representations of datasets. Colormap data visualizations ("colormaps") show patterns in datasets by mapping variations in color to variations in magnitude. When people interpret colormaps, they have expectations about how colors map to magnitude,…

This article proposes a pragmatic approach to data justice in education that draws upon Nancy Fraser's theory. The main argument is premised on the theoretical and practical superiority of a deontological framework for addressing algorithmic bias and harms, compared to ethical guidelines. The purpose of a deontological framework is to enable the…

Meta-analysts often encounter missing covariate values when estimating meta-regression models. In practice, ad hoc approaches involving data deletion have been widely used. The current study investigates the performance of different methods for handling missing covariates in meta-regression, including complete-case analysis (CCA), shifting-case…