National interest in using school climate as an accountability measure makes it important to understand how school leaders view and make use of school climate data. The purpose of this study was to investigate how school and district administrators use climate data in Virginia, where a statewide school climate survey is annually administered.…

Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…

This pilot study examined (a) the perceived barriers to creating high-quality social and emotional learning (SEL) IEP goals for autistic students without intellectual disabilities, and (b) the impact of using a data-driven SEL IEP goal builder--a key component of the Ivymount Social Cognition Instructional Package (IvySCIP)--on the quality of SEL…

Research information management (RIM) is a rapidly growing area of investment in US research universities. RIM systems that support the collection and use of research outputs metadata have been in place for many years. Globally, the RIM ecosystem is quite mature in locales where national research assessment exercises like the United Kingdom's…

Research Information Management (RIM) is a rapidly growing area of investment in US research universities, comprised of a variety of use cases, stakeholders, and products. This growth has been characteristically decentralized, resulting in silos, multiple systems, and frequent duplication of efforts at many institutions. This report is a two-part…

National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…

A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures…

In corequisite models of instruction, marginally prepared students are placed directly into college-level coursework, taught with a paired support course. Initial research suggests that such models yield significant improvements in the number of students passing credit-level mathematics when compared to previous models of prerequisite remediation.…

This publication is part of the Leading by Exemplar project, a multi-year study conducted by Bellwether Education Partners. In this project, every aspect of the Head Start exemplars' program design and practice was closely examined in an effort to understand each program's "secret sauce." Leading by Exemplar has three goals: (1) to…