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Fitzallen, Noleine; Watson, Jane – Mathematics Education Research Group of Australasia, 2023
This paper reports on students' experiences of describing and representing variation in hypothetical data. Fifty-six students (8-9 years-old) experienced collecting and working with quantitative data for two years as part of a STEM education project. The task described here was an end-of-year survey question, with three parts about a hypothetical…
Descriptors: Elementary School Students, STEM Education, Foreign Countries, Data Analysis
Watson, Jane; Fitzallen, Noleine; Wright, Suzie; Kelly, Ben – International Journal of Science and Mathematics Education, 2023
This report focuses on the ways in which 36 Grade 4 students recognized, explained, described, and employed variation during interviews conducted 1 month after participating in STEM-based activities in which they tested, adjusted, and re-tested catapults. An inductive thematic methodology was used for analysis of the interview transcripts to…
Descriptors: Elementary School Students, Grade 4, STEM Education, Student Attitudes
Saskia Schreiter; Markus Vogel – Educational Studies in Mathematics, 2025
The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center,…
Descriptors: Eye Movements, Statistical Distributions, Data Interpretation, Data Analysis
Ibrahim Oluwajoba Adisa; Danielle Herro; Oluwadara Abimbade; Golnaz Arastoopour Irgens – Information and Learning Sciences, 2024
Purpose: This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms. Design/methodology/approach: This paper describes a pedagogical approach that uses a data science…
Descriptors: Learner Engagement, Elementary School Students, Data Science, Computation
Ann Owens; Peter Rich – RSF: The Russell Sage Foundation Journal of the Social Sciences, 2023
Suburbs were once a haven for advantaged, White families to avoid city life and access high-status schools. This urban-suburban divide, however, has changed in recent decades as suburban communities (and their school districts) have diversified. This study provides an updated cross-sectional portrait of recent racial-ethnic segregation and…
Descriptors: Ethnic Groups, Equal Education, Urban Areas, Suburbs
Corrin, William; Zhu, Pei; Shih, Miki; Brown, Kevin Thaddeus, Jr.; Teres, Jed; Darrow, Catherine; Nichols, Austin; Lack, Kelly – National Center for Education Evaluation and Regional Assistance, 2022
These are the appendices for the report "The Effects of an Academic Language Program on Student Reading Outcomes." This study investigated WordGen Elementary, a program designed to improve fourth- and fifth-grade students' ability to understand and communicate academic language and their general reading skill. The program provider…
Descriptors: Academic Language, Reading Programs, Program Effectiveness, Reading Achievement
Dorottya Demszky; Heather Hill – Annenberg Institute for School Reform at Brown University, 2022
Classroom discourse is a core medium of instruction -- analyzing it can provide a window into teaching and learning as well as driving the development of new tools for improving instruction. We introduce the largest dataset of mathematics classroom transcripts available to researchers, and demonstrate how this data can help improve instruction.…
Descriptors: Elementary School Mathematics, Classroom Environment, Classroom Communication, Academic Records
Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Kuddar, Cagla; Cetin, Sevda – International Journal of Assessment Tools in Education, 2022
The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…
Descriptors: Mathematics Achievement, Structural Equation Models, Regression (Statistics), Achievement Tests
Egan, Laura; Tang, Judy H.; Ferraro, David; Erberber, Ebru; Tsokodayi, Yemurai; Stearns, Pat – National Center for Education Statistics, 2022
Trends in International Mathematics and Science Study (TIMSS) is an international comparative study designed to measure trends in mathematics and science achievement at grades 4 and 8, as well as to collect information about educational contexts (such as students' schools, teachers, and homes) that may be related to student achievement. TIMSS has…
Descriptors: Achievement Tests, Mathematics Achievement, International Assessment, Foreign Countries
Ferguson, Joseph Paul; Tytler, Russell; White, Peta – International Journal of Science Education, 2022
Reporting on a Grade 4 teaching and learning sequence, we highlight foundational constructs of measurement and data modelling which are fundamental to competence development in both science and mathematics. The sequence involved students generating and representing measures of their teacher's arm-span, with a focus on the invention and refinement…
Descriptors: Aesthetics, Data Analysis, Educational Philosophy, Teaching Methods
Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
Khanlari, Ahmad; Zhu, Gaoxia; Scardamalia, Marlene – Journal of Learning Analytics, 2019
Interdisciplinary studies foster integration of ideas across disciplines. The knowledge building pedagogy, with its 12 principles and associated technology, Knowledge Forum®, provides multifaceted support for linking ideas across disciplines and communities. This exploratory study aims to assess the extent to which elementary-school students…
Descriptors: Interdisciplinary Approach, Elementary School Students, Teaching Methods, Knowledge Level
Herget, Debbie; Dalton, Ben; Kinney, Saki; Smith, W. Zachary; Wilson, David; Rogers, Jim – National Center for Education Statistics, 2019
The Progress in International Reading Literacy Study (PIRLS) is an international comparative study of student performance in reading literacy at the fourth grade. PIRLS 2016 marks the fourth iteration of the study, which has been conducted every 5 years since 2001. New to the PIRLS assessment in 2016, ePIRLS provides a computer-based extension to…
Descriptors: Achievement Tests, Grade 4, Reading Achievement, Foreign Countries
Marland, Joshua; Harrick, Matthew; Sireci, Stephen G. – Educational and Psychological Measurement, 2020
Student assessment nonparticipation (or opt out) has increased substantially in K-12 schools in states across the country. This increase in opt out has the potential to impact achievement and growth (or value-added) measures used for educator and institutional accountability. In this simulation study, we investigated the extent to which…
Descriptors: Value Added Models, Teacher Effectiveness, Teacher Evaluation, Elementary Secondary Education