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Siobhan Reilley – Impacting Education: Journal on Transforming Professional Practice, 2024
The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…
Descriptors: Data Use, Data Collection, Data Analysis, Teacher Leadership
Chelsey Legacy; Andrew Zieffler; V. N. Vimal Rao; Robert Delmas – Statistics Education Research Journal, 2025
As ideas from data science become more prevalent in secondary curricula, it is important to understand secondary teachers' content knowledge and reasoning about complex data structures and modern visualizations. The purpose of this case study is to explore how secondary teachers make sense of mappings between data and visualizations, especially…
Descriptors: Secondary School Teachers, Visualization, Data, Data Use
Duncan Culbreth; Rebekah Davis; Cigdem Meral; Florence Martin; Weichao Wang; Sejal Foxx – TechTrends: Linking Research and Practice to Improve Learning, 2025
Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…
Descriptors: High School Students, COVID-19, Pandemics, Progress Monitoring
Sarah Klevan; Melanie Leung-Gagné; Tomoko M. Nakajima – Learning Policy Institute, 2024
Across the United States, there is an increased interest in improving school climate, reflecting a deepening understanding of the foundational role that school climate can play in supporting students' well-being, learning, and development. School climate is constructed from norms, expectations, and interpersonal relationships that come together to…
Descriptors: Educational Environment, Middle Schools, School Districts, Data Use
Quin-Anne Hinrichs; Chelsea R. Johnston; Laura Feuerborn; Ashli Tyre – Beyond Behavior, 2025
Implementation of a culturally responsive positive behavioral interventions and supports (PBIS) framework is associated with positive outcomes for secondary students when implemented schoolwide. Yet, educators often report more implementation challenges in secondary school as compared to elementary school settings. Difficulties obtaining student…
Descriptors: Behavior Modification, Positive Behavior Supports, Student Behavior, Behavior Problems
Wei Liu; Yingxue Wang – International Journal of Web-Based Learning and Teaching Technologies, 2025
Age is one of the important factors affecting individual differences in second language acquisition. The development of cognitive ability also has certain influence on second language acquisition, depending on whether this influence is positive or negative. This paper discusses the educational significance of the age factor in English teaching…
Descriptors: Secondary School Students, Secondary School Teachers, English (Second Language), Second Language Learning
Marianne van Dijke-Droogers; Paul Drijvers; Arthur Bakker – Mathematics Education Research Journal, 2025
In our data-driven society, it is essential for students to become statistically literate. A core domain within Statistical Literacy is Statistical Inference, the ability to draw inferences from sample data. Acquiring and applying inferences is difficult for students and, therefore, usually not included in the pre-10th-grade curriculum. However,…
Descriptors: Statistical Inference, Learning Trajectories, Grade 9, High School Students
Victoria Delaney; Victor R. Lee – Information and Learning Sciences, 2024
With increased focus on data literacy and data science education in K-12, little is known about what makes a data set preferable for use by classroom teachers. Given that educational designers often privilege authenticity, the purpose of this study is to examine how teachers use features of data sets to determine their suitability for authentic…
Descriptors: High School Teachers, Data Use, Information Literacy, Aesthetics
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Robin Clausen – Discover Education, 2025
Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…
Descriptors: Dropout Prevention, Data Analysis, Principals, School Counselors
Joshua Bleiberg; Tuan D. Nguyen – Annenberg Institute for School Reform at Brown University, 2025
Educator labor markets vary considerably across the country and can change quickly during recessions. We use data from the Quality Workforce Indicators (QWI) on educators in Elementary and Secondary Schools from 2000-01 to 2022-23. We demonstrate how to transform the quarter-level data in the QWI to construct valid educator labor market measures.…
Descriptors: Elementary School Teachers, Secondary School Teachers, Faculty Mobility, Teacher Burnout
Jennifer Kahn; Shiyan Jiang – Information and Learning Sciences, 2024
Purpose: While designing personally meaningful activities with data technologies can support the development of data literacies, this paper aims to focuses on the overlooked aspect of how learners navigate tensions between personal experiences and data trends. Design/methodology/approach: The authors report on an analysis of three student cases…
Descriptors: Visual Aids, Trend Analysis, Data Science, Secondary School Students
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
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
Reza Moeti; Abolfazl Rafiepour; Mohammad Reza Fadaee – Mathematics Teaching Research Journal, 2024
Despite the increasing interest in data science education in the world, its teaching is not included in the curricula (junior secondary) and there is little information about it. Google Trends is discussed as a tool and database in school data science. Also, in different subjects, students were able to create and interpret graphs using this tool.…
Descriptors: Foreign Countries, Data Science, Statistics Education, Middle School Students