NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20261
Since 202516
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 16 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Martin Abt; Katharina Loibl; Timo Leuders; Wim Van Dooren; Frank Reinhold – Educational Studies in Mathematics, 2025
In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…
Descriptors: College Students, Data Analysis, Graphs, Error Patterns
Peer reviewed Peer reviewed
Direct linkDirect link
Jae-Sang Han; Hyun-Joo Kim – Journal of Science Education and Technology, 2025
This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…
Descriptors: Performance, Automation, Scoring, Models
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Miriam Madsen – Discourse: Studies in the Cultural Politics of Education, 2025
While previous educational governance literature on datafication has paid attention to comparison across spatial entities like countries and schools, temporal comparison in terms of progression (including prediction) has received less attention. One of the material forms in which progression and prediction data are circulated is the visual form of…
Descriptors: Graphs, Prediction, Higher Education, Charts
Peer reviewed Peer reviewed
Direct linkDirect link
Lonneke Boels; Arthur Bakker; Wim Van Dooren; Paul Drijvers – Educational Studies in Mathematics, 2025
Many students persistently misinterpret histograms. This calls for closer inspection of students' strategies when interpreting histograms and case-value plots (which look similar but are different). Using students' gaze data, we ask: "How and how well do upper secondary pre-university school students estimate and compare arithmetic means of…
Descriptors: Secondary School Students, Learning Strategies, Data Interpretation, Graphs
Peer reviewed Peer reviewed
Direct linkDirect link
Kathryn Lanouette – Science Education, 2026
Creating, visualizing, and critiquing data are integral knowledge-building practices within science, as well as many other fields. Yet data is often treated as neutral and value-free, perpetuating narratives of science as a dispassionate discipline where data are merely extracted, repackaged, and distributed anew. As researchers and educators seek…
Descriptors: Data, Psychological Patterns, Visual Aids, Elementary School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Danielle R. Scharen; Erin McInerney; Lindsey H. Sachs; Meredith L. Hayes; P. Sean Smith – Mathematics Teacher: Learning and Teaching PK-12, 2025
School-based citizen science (SBCS) provides opportunities for teachers to purposefully integrate mathematics and science content and practices throughout the year. With SBCS projects, students have countless opportunities to apply their mathematics skills within the context of science data collection and sense making. This article details how a…
Descriptors: Citizenship, Science Education, Mathematics Skills, Grade 5
Peer reviewed Peer reviewed
Direct linkDirect link
Jihyun Rho; Martina A. Rau – Educational Psychology Review, 2025
Misleading data visualizations have become a significant issue in our information-rich world due to their negative impact on informed decision-making. Consequently, it is crucial to understand the factors that make viewers vulnerable to misleading data visualizations and to explore effective instructional supports that can help viewers combat the…
Descriptors: Visual Aids, Decision Making, Data Use, Deception
Peer reviewed Peer reviewed
Direct linkDirect link
Julian Schuessler; Peter Selb – Sociological Methods & Research, 2025
Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of…
Descriptors: Data Collection, Graphs, Error of Measurement, Statistical Bias
Peer reviewed Peer reviewed
Direct linkDirect link
Keith C. Radley; Evan H. Dart – Journal of Behavioral Education, 2025
Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged…
Descriptors: Graphs, Research Design, Visual Aids, Data Analysis
Sitti Maesuri Patahuddin; Andi Mulawakkan; Ajay Ramful – Mathematics Education Research Group of Australasia, 2025
This cross-sectional study examines participants' comprehension of line graphs at different career stages, comparing first-year and third-year pre-service teachers (PSTs) with in-service teachers (ISTs). A 23-item line graph task aligned with Curcio's framework--"Reading the data, Reading between the data, and Reading beyond the…
Descriptors: Graphs, Preservice Teachers, Teacher Education, Teaching Experience
Peer reviewed Peer reviewed
Direct linkDirect link
Abigail Stebbins; Amy Brass – Social Studies and the Young Learner, 2025
When teaching the Civil Rights Movement in elementary classrooms, heroic figures such as Rosa Parks and Martin Luther King Jr. tend to dominate the curricular landscape. While it is essential for students to learn about their contributions and struggles, it is equally important to frame the broader injustices they were combating. In this article,…
Descriptors: Social Studies, Civil Rights, Racism, Elementary Education
Peer reviewed Peer reviewed
Direct linkDirect link
Katherine N. Vela; Douglas W. Weber; Michelle Parslow; Kaitlin U. Campbell – Mathematics Teacher: Learning and Teaching PK-12, 2025
In today's data-rich world, students are constantly exposed to statistics through graphs and visuals in media, making data literacy an essential skill. Presented in this article, middle schoolers became entomologists in a 2-day garden-based STEM lesson, collecting and graphing data to explore how different graphs best represent scientific findings.
Descriptors: Middle School Students, STEM Education, Gardening, Graphs
Peer reviewed Peer reviewed
Direct linkDirect link
Sindhu Mathai; Parvathi Krishnan; Jaya Sreevalsan-Nair – Contemporary Education Dialogue, 2025
Graphical literacy or graphicacy is a critical component of scientific literacy. Graphs are used to integrate and represent complex sets of information requiring abstraction from perceptual experience. They form essential parts of the Mathematics and Science curriculum across school curricular stages. A key to developing meaningful pedagogic…
Descriptors: Multiple Literacies, Graphs, Elementary School Students, Middle School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Madhav Sharma; Andy Bowman – Journal of Information Systems Education, 2025
"Not only SQL" (NoSQL) databases have become widespread across organizations, enabling sophisticated, data-driven applications to be highly available, distributed, and cloud-based, such as e-commerce, social media, online multiplayer games, and video streaming. However, NoSQL is still sparsely found in MIS and analytics curricula. This…
Descriptors: Educational Technology, Technology Integration, Databases, Data Analysis
Previous Page | Next Page »
Pages: 1  |  2