Classroom quality measures, such as the Early Childhood Environment Rating Scale, Revised (ECERS-R), are widely used in research, practice, and policy. Increasingly, these uses have been for purposes not originally intended, such as contributing to consequential policy decisions. The current study adds to recent evidence of problems with the…

Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These…

As the standards movement continues into its third decade, there remains a need for alignment methodologies that can be broadly applied to study instruction and policy. This article reports on a series of development efforts meant to revise the Surveys of Enacted Curriculum (SEC) surveys and methods to study the implementation of new college- and…

School climate has received considerable attention in the literature and educational policy as a potential target for school improvement and school safety efforts. This paper provides a critical review and synthesis of the literature on school climate, with a particular focus on topics related to measurement, data collection, analysis, as well as…

Psychosocial functioning plays a key role in students' wellbeing and performance inside and outside of school. As such, techniques designed to measure and improve psychosocial functioning factor prominently in school-based service delivery and research. Given that the different contexts (e.g., school, home, community) in which students exist vary…

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,…

Assessing treatment integrity is essential to understanding how well school-based interventions are delivered. The assessment of treatment integrity is especially challenging for interventions that provide one-on-one peer support over the phone. To address this gap, we explored treatment integrity approaches used for the "Parent…

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…

Collection and analysis of students' writing samples on a large scale is a part of the research agenda of the emerging writing analytics community that promises to deliver an unprecedented insight into characteristics of student writing. Yet with a large scale often comes variability of contexts in which the samples were produced--different…

The results of educational research studies are only as accurate as the data used to produce them. Drawing on experiences conducting large-scale efficacy studies of classroom-based algebra interventions for community college and middle school students, I am developing practice-based data cleaning procedures to support scholars in conducting…

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…

The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…

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…

The field of learning analytics is rapidly developing techniques for using data captured during online learning. In this article, we develop an additional application: the use of analytics for improving implementation fidelity in a randomized controlled efficacy trial. In an efficacy trial, the goal is to determine whether an innovation has a…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…