Many national policy documents underscore the importance of 21st century skills, including critical thinking. In parallel, recent American frameworks for K-12 Science education call for the development of critical thinking skills in science, also referred to as science inquiry skills/practices. Assessment of these skills is necessary, as indicated…

The benefit of interleaving cognitive content has gained attention in recent years, specifically in mathematics education. The present study serves as a conceptual replication of previous work, documenting the interleaving effect within a middle school sample through brief homework assignments completed within ASSISTments, an adaptive tutoring…

Randomized experiments are often considered the strongest designs to study the impact of educational interventions. Perhaps the most prevalent class of designs used in large scale education experiments is the cluster randomized design in which entire schools are assigned to treatments. In cluster randomized trials (CRTs) that assign schools to…

Little research has examined individual linguistic features that influence English language learners (ELLs) test performance. Furthermore, research has yet to explore the relationship between the science strand of test items and the types of linguistic features the items include. Utilizing Differential Item Functioning, this study examines ELL…

We explore in this paper if automated scaffolding delivered via a pedagogical agent within a simulation can help students acquire data collection inquiry skills. Our initial analyses revealed that such scaffolding was effective for helping students who initially did not know two specific skills, designing controlled experiments and testing stated…

Students conducted inquiry using simulations within a rich learning environment for 4 science topics. By applying educational data mining to students' log data, assessment metrics were generated for two key inquiry skills, testing stated hypotheses and designing controlled experiments. Three models were then developed to analyze the transfer of…

There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled…

In this correlational study, we analyzed data from 71 Spanish-English biliterate students in grades 3 (n=21), 4 (n=23), and 5 (n=27) with the goal of investigating the applicability of the Simple View of Reading (Gough & Tunmer, 1986; Hoover & Gough, 1990) in English and in Spanish for this population. The simple view posits that decoding…

The goal of this study was to examine written translation as a means to: a) build on the theoretical notion that a bilingual individual's languages are shared; b) operationalize biliterate ability; and c) propose a new method of assessment for culturally and linguistically diverse students. Drawing from the fields of cognitive psychology and…

Background: Cluster randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…

When validating assessment models built with data mining, generalization is typically tested at the student-level, where models are tested on new students. This approach, though, may fail to find cases where model performance suffers if other aspects of those cases relevant to prediction are not well represented. We explore this here by testing if…

In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…

We present work toward automatically assessing and estimating science inquiry skills as middle school students engage in inquiry within a physical science microworld. Towards accomplishing this goal, we generated machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in…

Data-mined models often achieve good predictive power, but sometimes at the cost of interpretability. We investigate here if selecting features to increase a model's construct validity and interpretability also can improve the model's ability to predict the desired constructs. We do this by taking existing models and reducing the feature set to…

In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry skills in another domain (phase change). To do so, we leveraged educational data mining…