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Gottfried, Michael A.; Le, Vi-Nhuan; Kirksey, J. Jacob – Teachers College Record, 2020
Background: It is of grave concern that kindergartners are missing more school than students in any other year of elementary school; therefore, documenting which students are absent and for how long is of upmost importance. Yet, doing so for students with disabilities (SWDs) has received little attention. This study addresses this gap by examining…
Descriptors: Students with Disabilities, Attendance, Attendance Patterns, Teacher Aides
Smith, Bevan I.; Chimedza, Charles; Bührmann, Jacoba H. – International Journal of Artificial Intelligence in Education, 2020
Identifying students at risk of failing a course has potential benefits, such as recommending the At-Risk students to various interventions that could improve pass rates. The challenges however, are firstly in measuring how effective these interventions are, i.e. measuring treatment effects, and secondly, to not only predict overall (average)…
Descriptors: Artificial Intelligence, Man Machine Systems, Probability, Scoring
Carlson, Mary Alice; Arnold, Elizabeth G.; Bolte, Barbara – Mathematics Teacher: Learning and Teaching PK-12, 2020
Emphasis in teaching and learning statistics has shifted from memorizing formulas and procedures to investigating situations, creating models, and using data to understand problems. The Common Core State Standards for Mathematics (CCSSM) (NGA Center and CCSSO 2010) Grade 8 Statistics and Probability content standards drive this point home.…
Descriptors: Common Core State Standards, Mathematics Instruction, Teaching Methods, Statistics
Dempsey, Jack; Liu, Qiawen; Christianson, Kiel – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
Previous work has ostensibly shown that readers rapidly adapt to less predictable ambiguity resolutions after repeated exposure to unbalanced statistical input (e.g., a high number of reduced relative-clause garden-path sentences), and that these readers grow to disfavor the a priori more frequent (e.g. main verb) resolution after exposure (Fine,…
Descriptors: Probability, Cues, Syntax, Ambiguity (Semantics)
Bondurant, Liza; Odenwald, Sten – Science Teacher, 2020
Most likely a large number of students have heard of the Northern Lights (Aurora Borealis), and know that they are a phenomenon in the sky. Although they may not have seen the Northern Lights, most have probably seen other phenomena in the sky, such as a rainbow, shooting star, or super moon. These experiences provide an opportunity for students…
Descriptors: Science Instruction, Mathematics Instruction, Equations (Mathematics), Prediction
Ernst, Heather; Morton, Anna – Australian Mathematics Education Journal, 2020
This article describes several ways to connect probability to other topics within mathematics, over a range of year levels, and across the curriculum. It includes a description of common issues and misconceptions, and practical learning activities to address them.
Descriptors: Probability, Mathematics Instruction, Misconceptions, Relevance (Education)
Kim, Irang; Dababnah, Sarah; Lee, Jaegoo – Journal of Autism and Developmental Disorders, 2020
We examined the relationship between family resilience and parenting stress among parents of children with autism spectrum disorder, with a specific focus on race/ethnicity as a moderator. Multivariate models indicated that family resilience was associated with parenting stress. Race/ethnicity significantly moderated the relationship between…
Descriptors: Resilience (Psychology), Child Rearing, Stress Variables, Parents
Groth, Randall E.; Bergner, Jennifer A.; Austin, Jathan W. – Journal for Research in Mathematics Education, 2020
Normative discourse about probability requires shared meanings for disciplinary vocabulary. Previous research indicates that students' meanings for probability vocabulary often differ from those of mathematicians, creating a need to attend to developing students' use of language. Current standards documents conflict in their recommendations about…
Descriptors: Mathematics Education, Mathematics Instruction, Probability, Vocabulary Development
Ramesh, Arti; Goldwasser, Dan; Huang, Bert; Daume, Hal; Getoor, Lise – IEEE Transactions on Learning Technologies, 2020
Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…
Descriptors: Online Courses, Learner Engagement, Student Behavior, Success
Fuchsman, Dillon; Sass, Tim R.; Zamarro, Gema – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2020
Teacher turnover has adverse consequences for student achievement and imposes large financial costs for schools. Some have argued that high-stakes testing may lower teachers' satisfaction with their jobs and could be a major contributor to teacher attrition. In this paper, we exploit changes in the tested grades and subjects in Georgia to study…
Descriptors: Testing, Faculty Mobility, Teacher Distribution, High Stakes Tests
Paul T. von Hippel; Laura Bellows – Annenberg Institute for School Reform at Brown University, 2020
At least sixteen US states have taken steps toward holding teacher preparation programs (TPPs) accountable for teacher value-added to student test scores. Yet it is unclear whether teacher quality differences between TPPs are large enough to make an accountability system worthwhile. Several statistical practices can make differences between TPPs…
Descriptors: Teacher Effectiveness, Teacher Education Programs, Scores, Accountability
Mathes, Tim; Kuss, Oliver – Research Synthesis Methods, 2018
Meta-analyses often include only a small number of studies ([less than or equal to]5). Estimating between-study heterogeneity is difficult in this situation. An inaccurate estimation of heterogeneity can result in biased effect estimates and too narrow confidence intervals. The beta-binominal model has shown good statistical properties for…
Descriptors: Comparative Analysis, Meta Analysis, Probability, Statistical Analysis
Hong, Guanglei; Qin, Xu; Yang, Fan – Journal of Educational and Behavioral Statistics, 2018
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Descriptors: Statistical Inference, Probability, Statistical Bias, Statistical Analysis
Liu, Ren; Qian, Hong; Luo, Xiao; Woo, Ada – Educational and Psychological Measurement, 2018
Subscore reporting under item response theory models has always been a challenge partly because the test length of each subdomain is limited for precisely locating individuals on multiple continua. Diagnostic classification models (DCMs), providing a pass/fail decision and associated probability of pass on each subdomain, are promising…
Descriptors: Classification, Probability, Pass Fail Grading, Scores
Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2018
This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Difficulty Level