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Turner, Simon Lee; Korevaar, Elizabeth; Cumpston, Miranda S.; Kanukula, Raju; Forbes, Andrew B.; McKenzie, Joanne E. – Research Synthesis Methods, 2023
Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis. While publications of ITS rarely provide…
Descriptors: Quasiexperimental Design, Graphs, Accuracy, Computation
Gafny, Ronit; Ben-Zvi, Dani – Teaching Statistics: An International Journal for Teachers, 2023
In recent years, big data has become ubiquitous in our day-to-day lives. Therefore, it is imperative for educators to integrate nontraditional (big) data into statistics education to ensure that students are prepared for a big data reality. This study examined graduate students' expressions of uncertainty while engaging with traditional and…
Descriptors: Student Attitudes, Data Science, Data Analysis, Models
Guy Bendermacher; Mirjam oude Egbrink; Diana Dolmans – Interdisciplinary Journal of Problem-based Learning, 2023
Problem-based learning (PBL) can take many different shapes but has as a common denominator that it builds on the principles of collaborative, constructive, contextual, and self-directed learning. Systematic review approaches that aim to provide insight in what features make PBL work generally fall short, as they tend to disregard the influential…
Descriptors: Problem Based Learning, Research Methodology, Realism, Program Effectiveness
Schildkamp, Kim; Datnow, Amanda – Leadership and Policy in Schools, 2022
Because learning from failures is just as important as learning from successes, we used qualitative case study data gathered in the Netherlands and the United States to examine instances in which data teams struggle to contribute to school improvement. Similar factors in both the Dutch and U.S. case hindered the work of the data teams, such as…
Descriptors: Foreign Countries, Educational Improvement, Data Use, Failure
Yang, Chunsheng; Chiang, Feng-Kuang; Cheng, Qiangqiang; Ji, Jun – Journal of Educational Computing Research, 2021
Machine learning-based modeling technology has recently become a powerful technique and tool for developing models for explaining, predicting, and describing system/human behaviors. In developing intelligent education systems or technologies, some research has focused on applying unique machine learning algorithms to build the ad-hoc student…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Data Use, Models
Krista Bixler; Marjorie Ceballos – Leadership and Policy in Schools, 2025
Instructional leadership is a complex dimension, which requires that principals possess expertise in goal setting, leading the instructional program, and creating the conditions for a successful school environment. Effective instructional leaders manage the instructional program by planning, coordinating, and evaluating the work of teachers and…
Descriptors: Principals, Instructional Leadership, Artificial Intelligence, Educational Technology
Robert M. Johnstone – Educational Considerations, 2025
This article explores utilizing a post-graduation success lens to help community college leaders frame the challenges of achieving equitable improvement for their students. Specifically, it posits that providing and exploring customized labor market data presented in an accessible format can help institutional leaders provide a "true…
Descriptors: Community College Students, College Graduates, Outcomes of Education, Success
Zeynab (Artemis) Mohseni; Italo Masiello; Rafael M. Martins – Education and Information Technologies, 2024
There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…
Descriptors: Elementary School Students, Data, Individual Development, Learning Trajectories
Erickson, Tim; Chen, Ernest – Teaching Statistics: An International Journal for Teachers, 2021
This paper describes a short module for introducing data science to senior school students or other data-science beginners. The design focuses on "data moves." Students use CODAP to do their work.
Descriptors: Data, Statistics Education, Novices, Data Analysis
Aimee Jacobs; Jacquelin J. Curry; Concetta A. DePaolo; Fernando Parra – Journal of Information Systems Education, 2024
This manuscript describes the use of real data applied to a fictional real-estate firm for teaching data visualization to university students. In the case study, students employ data analytic techniques in Tableau to clean, organize, and analyze real estate data. By creating visualizations, students address several questions about how selling…
Descriptors: Visualization, Housing, Computer Software, Data Use
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
Wei Liu – International Journal of Research & Method in Education, 2024
Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it…
Descriptors: Qualitative Research, Cognitive Processes, Classification, Data Analysis
Li, Ak Wai; Sinnamon, Luanne S.; Kopak, Rick – Information and Learning Sciences, 2022
Purpose: The purpose of this study is to explore open data portals as data literacy learning environments. The authors examined the obstacles faced and strategies used by university students as non-expert open data portal users with different levels of data literacy, to inform the design of portals intended to scaffold informal and situated…
Descriptors: Data Collection, Multiple Literacies, Data, College Students
Center for IDEA Early Childhood Data Systems (DaSy), 2022
The value of data is increasingly recognized by organizations and programs, including Individuals with Disabilities Education Act (IDEA) Part C and Part B 619 programs. Data can help Part C and Part B 619 program coordinators, data managers and staff improve outcomes for children and families by strengthening their understanding of the needs of…
Descriptors: Equal Education, Educational Legislation, Federal Legislation, Students with Disabilities
Nehyba, Jan; Štefánik, Michal – Education and Information Technologies, 2023
Social sciences expose many cognitively complex, highly qualified, or fuzzy problems, whose resolution relies primarily on expert judgement rather than automated systems. One of such instances that we study in this work is a reflection analysis in the writings of student teachers. We share a hands-on experience on how these challenges can be…
Descriptors: Models, Language, Reflection, Writing (Composition)