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…

Single-case designs (SCDs) are a class of research methods for evaluating the effects of academic and behavioral interventions in educational and clinical settings. Although visual analysis is typically the first and main method for primary analysis of data from SCDs, quantitative methods are useful for synthesizing results and drawing systematic…

The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

Though qualitative research has become more prevalent in practice over the last 30 years, there is still considerable uncertainty among researchers regarding how to ensure inter-rater consistency when teams are tasked with coding qualitative data. In this article, we offer an explanation of a methodology our qualitative team used to achieve…

Traditional statistical model evaluation typically relies on goodness-of-fit testing and quantifying model complexity by counting parameters. Both of these practices may result in overfitting and have thereby contributed to the generalizability crisis. The information-theoretic principle of minimum description length addresses both of these…

Purpose: Comparative data of autism-sensitive standardized measures of emotion regulation and lability, describing percentage change over time for populations of young autistic children, are currently publicly unavailable. We propose publication of such data as a support for future therapeutic intervention studies. Methods: We generate and present…

Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the…

Mental health organizations that serve youth are under pressure to adopt measurement-based care (MBC), defined as the continuous collection of client-report data used to support clinical decision making as part of standard care. However, few frameworks exist to help leadership ascertain how to select an MBC approach for a clinical setting. This…

The exponential growth of scientific publications increases the effort required to identify relevant articles. Moreover, the scale of studies is a frequent barrier to research as the majority of studies are low or medium-scaled and do not generalize well while lacking statistical power. As such, we introduce an automated method that supports the…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Clients display considerable variations in functioning across the contexts that encompass their social environments (e.g., home, school/workplace, peer interactions). No single measurement method can fully capture these variations. Yet, assessors must balance the need to accurately capture clients' clinical presentations, and at the same time…

Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…

More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…

The COVID-19 outbreak emphasizes the need for alternative methods for data gathering and collaboration among researchers in a virtual research environment. One experimental design that is well suited in a social distancing research context is the single-case experimental design (SCD). SCDs can handle disruptions as: (a) they do not require large…

The quantitative assessment of eye tracking data quality is critical for ensuring accuracy and precision of gaze position measurements. However, researchers often report the eye tracker's optimal manufacturer's specifications rather than empirical data about the accuracy and precision of the eye tracking data being presented. Indeed, a recent…