Comparative Judgement (CJ) aims to improve the quality of performance-based assessments by letting multiple assessors judge pairs of performances. CJ is generally associated with high levels of reliability, but there is also a large variation in reliability between assessments. This study investigates which assessment characteristics influence the…

This research study provides an examination of the relatively new fields of Data Analytics and Data Science. We compare word rates in Data Analytics and Data Science documents to determine which concepts are mentioned most often. The most frequent concept in both fields is "data." The word rate for "data" is more than twice the…

Heterogeneity in meta-analysis is most commonly estimated using a moment-based approach described by DerSimonian and Laird. However, this method has been shown to produce biased estimates. Alternative methods to estimate heterogeneity include the restricted maximum likelihood approach and those proposed by Paule and Mandel, Sidik and Jonkman, and…

Two journals reflecting the interests and concerns of music educators are "Music Educators Journal (MEJ)" and "Philosophy of Music Education Review (PMER)". The purpose of this study was to explore the interests of P--12 music teachers and university faculty as represented by the topics of articles in "MEJ" and…

Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

We performed a systematic literature search regarding maternal diabetes before and during pregnancy and the risk of autism spectrum disorders (ASD) in the offspring. Of the 178 potentially relevant articles, 12 articles including three cohort studies and nine case-control studies were included in the meta-analysis. Both the meta-analyses of cohort…

This study aims to generate a conceptual framework for specialized Science, Technology, Engineering, and Mathematics (STEM) schools. To do so, we focused on literature and found specialized STEM schools have existed for over 100 years and recently expanded nationwide. The current perception for these schools can be described as unique environments…

This study aims to generate a conceptual framework for specialized Science, Technology, Engineering, and Mathematics (STEM) schools. To do so, we focused on literature and found specialized STEM schools have existed for over 100 years and recently expanded nationwide. The current perception for these schools can be described as unique environments…

Examines research on the observed values of retrieval effectiveness obtained in searches of files of nearest neighbor document clusters. Results show interdocument similarities used to generate nearest-neighbor clusters are significantly different from randomly generated clusters. (Contains 14 references.) (EAM)

I. Klugkist, O. Laudy, and H. Hoijtink (2005) presented a Bayesian approach to analysis of variance models with inequality constraints. Constraints may play 2 distinct roles in data analysis. They may represent prior information that allows more precise inferences regarding parameter values, or they may describe a theory to be judged against the…

Reports information retrieval experiments comparing the performance of a probabilistic retrieval model that incorporates interdocument links with the simpler spreading activation strategy. Results indicated that the overall improvement obtained by including hypertext links in the retrieval model was low. (30 references) (EA)

This Brief reports on a new study that begins to fill this research gap. Using longitudinal unit record transcript data on a cohort of first-time community college students in Florida, the study sought to determine whether remedial pathways, such as enrolling in a developmental math course, and enrollment milestones, such as completing a certain…

In machine learning there is considerable interest in techniques which improve planning ability. Initial investigations have identified a wide variety of techniques to address this issue. Progress has been hampered by the utility problem, a basic tradeoff between the benefit of learned knowledge and the cost to locate and apply relevant knowledge.…