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Jing Liu; Megan Kuhfeld; Monica Lee – Annenberg Institute for School Reform at Brown University, 2023
Noncognitive constructs such as self-efficacy, social awareness, and academic engagement are widely acknowledged as critical components of human capital, but systematic data collection on such skills in school systems is complicated by conceptual ambiguities, measurement challenges and resource constraints. This study addresses this issue by…
Descriptors: Student Behavior, Predictor Variables, Predictive Validity, Academic Achievement
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
Holzman, Brian; Duffy, Horace – Houston Education Research Consortium, 2020
Part II of the Houston Longitudinal Study on the Transition to College and Work (HLS) examined potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college. The study used administrative data from the Houston Independent School District (HISD) and tracked two…
Descriptors: Enrollment, At Risk Students, Urban Schools, Predictor Variables
Holzman, Brian; Duffy, Horace – Houston Education Research Consortium, 2020
This report examined three potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college: (1) Chicago: Designed to predict high school graduation; based on earning six course credits--the minimum to advance to the next grade in HISD--and having at most one semester…
Descriptors: Enrollment, At Risk Students, Urban Schools, Predictor Variables
Holzman, Brian; Duffy, Horace – Houston Education Research Consortium, 2020
These are the appendices for "Transitioning to College and Work. Part 2: A Study of Potential Enrollment Indicators," which examined potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college. The study used administrative data from the Houston…
Descriptors: Enrollment, At Risk Students, Urban Schools, Predictor Variables
Emam, Mahmoud Mohamed – Emotional & Behavioural Difficulties, 2018
Identification of children who exhibit emotional and behavioural difficulties (EBDs) has been prioritized in several countries in the Middle East and North Africa (MENA) region including Oman. Research showed that cognitive attribution processes are biased and defective in atypical populations such as students with learning disabilities (LD). The…
Descriptors: Predictor Variables, Emotional Disturbances, Behavior Problems, Learning Disabilities
Penk, Christiane; Richter, Dirk – Educational Assessment, Evaluation and Accountability, 2017
Since the turn of the century, an increasing number of low-stakes assessments (i.e., assessments without direct consequences for the test-takers) are being used to evaluate the quality of educational systems. Internationally, research has shown that low-stakes test results can be biased due to students' low test-taking motivation and that…
Descriptors: Test Wiseness, Student Motivation, Academic Achievement, Cognitive Tests
Northey, Mary; McCutchen, Deborah; Sanders, Elizabeth A. – Reading and Writing: An Interdisciplinary Journal, 2016
Morphological skills have previously been found to reliably predict reading skill, including word reading, vocabulary, and comprehension. However, less is known about how morphological skills might contribute to writing skill, aside from its well-documented role in the development of spelling. This correlational study examines whether…
Descriptors: Essays, Childrens Writing, Morphology (Languages), Writing Skills
Knight, George P.; Carlo, Gustavo; Mahrer, Nicole E.; Davis, Alexandra N. – Child Development, 2016
The socialization of cultural values, ethnic identity, and prosocial behaviors is examined in a sample of 749 Mexican-American adolescents, ages 9-12; M (SD) = 10.42 years (0.55); 49% female, their mothers, and fathers at the 5th, 7th, and 10th grades. Parents' familism values positively predicted their ethnic socialization practices. Mothers'…
Descriptors: Mexican Americans, Adolescents, Social Values, Ethnicity
Peters, S. Colby; Woolley, Michael E. – Children & Schools, 2015
Data from the School Success Profile generated by 19,228 middle and high school students were organized into three broad categories of risk and protective factors--control, support, and challenge--to examine the relative and combined power of aggregate scale scores in each category so as to predict academic success. It was hypothesized that higher…
Descriptors: Academic Achievement, Success, Risk, Risk Assessment
Truckenmiller, Adrea J.; Petscher, Yaacov; Gaughan, Linda; Dwyer, Ted – Regional Educational Laboratory Southeast, 2016
District and state education leaders frequently use screening assessments to identify students who are at risk of performing poorly on end-of-year achievement tests. This study examines the use of a universal screening assessment of reading skills for early identification of students at risk of low achievement on nationally normed tests of reading…
Descriptors: Prediction, Predictive Validity, Predictor Variables, Mathematics Achievement
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
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…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
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…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Johnson, Ursula Y.; Hull, Darrell M. – Journal of Educational Research, 2014
The authors examined science achievement growth at Grades 3, 5, and 8 and parent school involvement at the same time points using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999. Data were analyzed using cross-classified multilevel latent growth curve modeling with time invariant and varying covariates. School-based…
Descriptors: Science Achievement, Parent Participation, Grade 3, Grade 5
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