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Jane Buckley; Elyse Postlewaite; Thomas Archibald; Miriam R. Linver; Jennifer Brown Urban – American Journal of Evaluation, 2025
The purpose of this article is to offer both theoretical and practical support to evaluation professionals preparing to facilitate the utilization phase of evaluation with a program or organization team. The Systems Evaluation Protocol for Participatory Data Use (SEPPDU) presented here is rooted in a partnership approach to evaluation and is…
Descriptors: Data Use, Evaluation Utilization, Data Interpretation, Decision Making
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Mostafa M. Samy; Mohamed A. Metwally; Mahmoud Ashry; Wael M. Elmayyah – Measurement: Interdisciplinary Research and Perspectives, 2025
Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…
Descriptors: Engines, Power Technology, Data Collection, Data Interpretation
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Margaret Marchant; Ethan Eliason – Journal of Education for Business, 2024
Undergraduate economics programs prepare students for future careers by developing competency working with data, or "data literacy." Our research examined the data literacy components of undergraduate economics programs at R1 and R2 universities in the United States (N = 190). We developed a protocol with core data skills and coded…
Descriptors: Undergraduate Students, Economics Education, Data Collection, Data Interpretation
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Iva Božovic – Journal of Political Science Education, 2024
This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…
Descriptors: Data Use, Teaching Methods, Data, Information Literacy
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Kim Schildkamp; Anders Ruud Fosnæs; Yngve Lindvig; Jarl Inge Wærness – Journal of Professional Capital and Community, 2025
Purpose: Specific forms of data use in schools, particularly those that involve students in interpreting and utilizing the data about themselves, are gaining recognition. This exploratory qualitative study focused on students' involvement in the use of data coming from a national survey. Design/methodology/approach: In three best-practice schools,…
Descriptors: Student Participation, Participative Decision Making, Data Use, Data Analysis
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Adolfsson, Carl-Henrik; Håkansson, Jan – Leadership and Policy in Schools, 2023
From a new institutional theoretical perspective, this article explores school actors' sense-making linked to data-based decision making (DBDM) policy in general and processes of data analysis in particular. The study revealed how actors' interpretation of and response to DBDM pointed to strong and weak couplings between and within the local…
Descriptors: Data Analysis, Educational Improvement, Decision Making, Data Interpretation
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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
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Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
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Ioana-Elena Oana; Carsten Q. Schneider – Sociological Methods & Research, 2024
The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…
Descriptors: Robustness (Statistics), Qualitative Research, Comparative Analysis, Decision Making
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William Norris; Roger Hanagriff; Don Edgar; Kirk Swortzel – Journal of Agricultural Education, 2025
Supervised Agricultural Experience (SAE) has been a critical component of School-Based Agricultural Education (SBAE) for decades. Formally called the 'home project', Rufus Stimson developed the concept of SAE in the early 20th century. This work-based learning concept provides students with experiential instruction that strengthens their…
Descriptors: Agricultural Education, Agriculture Teachers, Field Experience Programs, Experiential Learning
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Jin, Hui; Hokayem, Hayat; Cisterna, Dante – Research in Science & Technological Education, 2023
Background: New technology and increased collaboration have revolutionized how scientists work with data. This creates a need to identify new aspects of working with scientific data that are important for K-12 students to learn. Purpose: To address this need, we conducted a study with practicing scientists and K-12 science teachers. The purpose of…
Descriptors: Scientists, Science Teachers, Elementary School Teachers, Secondary School Teachers
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Jennings, Austin S. – Elementary School Journal, 2023
Teachers' data literacy and interpretive process are critical to understanding how they make sense of data. However, little is known about how mental representations shape and evolve in response to teachers' interpretive process. In the present study, I model and explore this recursive relationship between teachers' cognitive framing and…
Descriptors: Data Interpretation, Cognitive Processes, Academic Achievement, Student Evaluation
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Prerna Srigyan; Kim Fortun – Science & Education, 2025
Research in cultural anthropology and the interdisciplinary field of science and technology studies (STS) has demonstrated that environmental disasters are not only techno-scientifically and socio-politically complex but also epistemically complex -- involving perspectival diversity; multiple, often conflicting forms of evidence; data gaps and…
Descriptors: Case Studies, Environmental Education, Natural Disasters, Justice
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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
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Mária Cujdíková; Ivan Kalaš – Informatics in Education, 2025
Tables are fundamental tools for handling data and play a crucial role in developing both computational thinking (CT) and mathematical thinking (MT). Despite this, they receive limited attention in research and design. This study investigates pupils' attitudes toward and approaches to working with tables in informatics education, focusing on the…
Descriptors: Foreign Countries, Elementary School Curriculum, Programming, Computation
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