Publication Date
In 2025 | 12 |
Since 2024 | 35 |
Since 2021 (last 5 years) | 117 |
Since 2016 (last 10 years) | 485 |
Descriptor
Source
Author
Zhang, Mo | 5 |
Deane, Paul | 4 |
Allen, Jeff | 3 |
Bennett, Randy E. | 3 |
Sinharay, Sandip | 3 |
Van Norman, Ethan R. | 3 |
Algina, James | 2 |
Amendum, Steven J. | 2 |
Arend M. Kuyper | 2 |
Armour, Mim, Ed. | 2 |
Barnes, Tiffany | 2 |
More ▼ |
Publication Type
Education Level
Location
Texas | 14 |
Turkey | 12 |
California | 7 |
Canada | 7 |
Maryland | 7 |
Minnesota | 7 |
Tennessee | 7 |
Arizona | 6 |
Florida | 6 |
Indiana | 6 |
New Jersey | 6 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Meets WWC Standards without Reservations | 1 |
Meets WWC Standards with or without Reservations | 2 |
Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
Toshiya Arakawa; Haruki Miyakawa – Technology, Knowledge and Learning, 2025
Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…
Descriptors: Data Science, Educational Games, Statistics Education, Foreign Countries
Marwan, Samiha; Shi, Yang; Menezes, Ian; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2021
Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…
Descriptors: Expertise, Models, Feedback (Response), Identification
Bret Bailey – ProQuest LLC, 2024
The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…
Descriptors: Academic Achievement, Grade 6, Data, Mathematics
Vaccarello, Cara; Kratochwill, Thomas R.; Asmus, Jennifer M. – Journal of Educational and Psychological Consultation, 2023
We examined the outcomes of elementary school-based problem-solving teams (PSTs) who participated in a multi-component consultation focused on enhancing systematic problem solving. Consultation provided to each PST included training in the use of a problem-solving protocol (i.e., "Outcomes: Planning Monitoring, and Evaluating"…
Descriptors: Elementary School Teachers, Problem Solving, Consultation Programs, Coaching (Performance)
Zhao, Xue; Lee, Rebecca E.; Ledoux, Tracey A.; Hoelscher, Deanna M.; McKenzie, Thomas L.; O'Connor, Daniel P. – Journal of School Health, 2022
Background: This study describes a method for harmonizing data collected with different tools to compute a rating of compliance with national recommendations for school physical activity (PA) and nutrition environments. Methods: We reviewed questionnaire items from 84 elementary schools that participated in the Childhood Obesity Research…
Descriptors: Data Collection, Data Analysis, Computation, Compliance (Legal)
Yaosheng Lou; Kimberly F. Colvin – Discover Education, 2025
Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…
Descriptors: Educational Research, Data Collection, Performance, Prediction
Fernando Rios-Avila; Michelle Lee Maroto – Sociological Methods & Research, 2024
Quantile regression (QR) provides an alternative to linear regression (LR) that allows for the estimation of relationships across the distribution of an outcome. However, as highlighted in recent research on the motherhood penalty across the wage distribution, different procedures for conditional and unconditional quantile regression (CQR, UQR)…
Descriptors: Regression (Statistics), Research Methodology, Alternative Assessment, Models
Doran, Elizabeth; Reid, Natalie; Bernstein, Sara; Nguyen, Tutrang; Dang, Myley; Li, Ann; Kopack Klein, Ashley; Rakibullah, Sharika; Scott, Myah; Cannon, Judy; Harrington, Jeff; Larson, Addison; Tarullo, Louisa; Malone, Lizabeth – Office of Planning, Research and Evaluation, 2022
Head Start is a national program that helps young children from families with low income get ready to succeed in school. It does this by working to promote their early learning and health and their families' well-being. The Head Start Family and Child Experiences Survey (FACES) provides national information about Head Start programs and…
Descriptors: Federal Programs, Low Income Students, Social Services, Children
Jiawei Xiong; George Engelhard; Allan S. Cohen – Measurement: Interdisciplinary Research and Perspectives, 2025
It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…
Descriptors: Responses, Test Items, Test Format, Grade 8
Mihyun Son; Minsu Ha – Education and Information Technologies, 2025
Digital literacy is essential for scientific literacy in a digital world. Although the NGSS Practices include many activities that require digital literacy, most studies have examined digital literacy from a generic perspective rather than a curricular context. This study aimed to develop a self-report tool to measure elements of digital literacy…
Descriptors: Test Construction, Measures (Individuals), Digital Literacy, Scientific Literacy
Ho, Andrew D. – AERA Open, 2020
The Stanford Education Data Archive (SEDA) launched in 2016 to provide nationally comparable, publicly available test score data for U.S. public school districts. I introduce a special collection of six articles that each use SEDA to lend their questions and findings a national scope. Together, these articles demonstrate a range of uses of SEDA…
Descriptors: Archives, Scores, Public Schools, School Districts
Marion, S. F.; Gonzales, D.; Wiener, R.; Peltzman, A. – National Center for the Improvement of Educational Assessment, 2020
State policymakers are confronting well-documented intersecting crises -- medical, economic, and racial -- with especially dire implications for educational equity. State education leaders face a moral urgency to both understand and respond to the challenges students are experiencing and to do so in ways that address burgeoning equity gaps.…
Descriptors: State Policy, Educational Opportunities, Program Evaluation, Summative Evaluation
Trevor K. M. Day; Arielle Borovsky; Donna Thal; Jed T. Elison – Developmental Science, 2025
The MacArthur-Bates Communicative Development Inventories (CDI) are widely used, parent-report instruments of language acquisition. Here, we focus on the word-inventory sections of the instruments, and show two different approaches to modeling CDI data, based on real-world needs. First, we show that Words & Gestures data collected…
Descriptors: Language Skills, Measures (Individuals), Children, Models
Sijia Huang; Seungwon Chung; Carl F. Falk – Journal of Educational Measurement, 2024
In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…
Descriptors: Response Style (Tests), Classification, Data, Models