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…

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…

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…

Schools are increasingly turning towards restorative practices as a pathway to building schools with stronger relationships, justice, and equity. While effectiveness studies are increasing, too little attention is focused on evaluating implementation. This resources is for audiences who evaluate implementation of whole school restorative practices…

Well-designed digital games hold promise as effective learning environments. However, designing games that support both learning and engagement without disrupting flow is quite tricky. In addition to including various game design features (e.g., interactive problem solving, adaptive challenges, and player control of gameplay) to engage players,…

The Learning Target Rating Scale (LTRS) is a measure designed to evaluate the quality of teacher-developed learning targets for embedded instruction for early learning. In the present study, we examined the measurement dependability of LTRS scores by conducting a generalizability study (G-study). We used a partially nested, three-facet model to…

How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…