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Alderson, David L. – INFORMS Transactions on Education, 2022
This article describes the motivation and design for introductory coursework in computation aimed at midcareer professionals who desire to work in data science and analytics but who have little or no background in programming. In particular, we describe how we use modern interactive computing platforms to accelerate the learning of our students…
Descriptors: Curriculum Design, Introductory Courses, Computation, Data Science
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Švábenský, Valdemar; Vykopal, Jan; Celeda, Pavel; Tkácik, Kristián; Popovic, Daniel – Education and Information Technologies, 2022
Hands-on cybersecurity training allows students and professionals to practice various tools and improve their technical skills. The training occurs in an interactive learning environment that enables completing sophisticated tasks in full-fledged operating systems, networks, and applications. During the training, the learning environment allows…
Descriptors: Computer Security, Information Security, Training, Data Collection
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Heinzman, Erica – Statistics Education Research Journal, 2022
Many important voices--including The National Council for Teachers of Mathematics (NCTM), the Dana Center's Launch Years initiative, and others--advocate for expanding the traditional course offerings in high school mathematics and statistics to include courses such as the Introduction to Data Science (IDS). To date, the research on the IDS course…
Descriptors: High School Students, Student Experience, Student Attitudes, Self Efficacy
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Inan, Elvan; Mert Uyangor, Sevinç – Participatory Educational Research, 2022
The aim of this research is to examine the postgraduate studies conducted in the field of mathematics education with individuals diagnosed as gifted and talented students in Türkiye. For this purpose, master's and doctoral studies in the database of the National Thesis Center of the Council of Higher Education [CHE] of Türkiye were examined. The…
Descriptors: Foreign Countries, Masters Theses, Doctoral Dissertations, Mathematics Education
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Reeves, Todd D.; Wei, Dan; Hamilton, Valerie – Educational Forum, 2022
Non-academic factors such as school climate, grit, and growth mindset are receiving much attention in recent education policy and practice. Within this context, this study (N = 425) describes the distribution of U.S. in-service teachers' access to and use of 10 categories of non-academic data. Findings indicate that in-service teachers vary widely…
Descriptors: Access to Information, Data Use, Decision Making, Educational Environment
Data Quality Campaign, 2022
State legislators have the opportunity to create and support legislation that positions data as a tool to help decisionmakers at all levels take action to support student success. This checklist can serve as a guide to crafting legislation that addresses education data. It applies specifically to education data legislation which includes bills…
Descriptors: State Legislation, Data Collection, Data Analysis, Educational Policy
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Bhavik Anil Patel – Journal of Chemical Education, 2022
Accuracy and precision are measures of experimental error and are fundamental to most chemical analysis laboratory classes. Assessment of accuracy and precision is often based on the comprehension of the results generated by students rather than on the quality of the data generated. This activity focused on developing a chemical analysis…
Descriptors: Chemistry, Science Laboratories, Accuracy, Data
Laura Anderson; Hannah Jarmolowski; Marguerite Roza; Jessica Swanson – National Comprehensive Center, 2022
"Leading Thoughtful Conversations about School-by-School Spending Data" is a product of a federally-funded study to support the US Department of Education and the field more broadly to understand what data visualizations work to fuel thoughtful conversation among district and school leaders on financial strategy and management. This…
Descriptors: Educational Finance, Educational Equity (Finance), Data Interpretation, Visualization
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Edoardo Saccenti – Teaching Statistics: An International Journal for Teachers, 2024
Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions…
Descriptors: Factor Analysis, Data Analysis, Information Literacy, Visualization
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Sean McGrath; XiaoFei Zhao; Omer Ozturk; Stephan Katzenschlager; Russell Steele; Andrea Benedetti – Research Synthesis Methods, 2024
When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to…
Descriptors: Statistical Analysis, Meta Analysis, Data Analysis, Sampling
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Ulrich A. Hoensch – PRIMUS, 2024
We present a concrete situation where there is a difference between the theoretical security of a cipher and its limitations when implemented in practice. Specifically, when entering a PIN, smudges on the keypad substantially reduce its security. We show how the number of possible keys in the presence of the "smudge attack" can be…
Descriptors: Information Security, Computer Security, Coding, Undergraduate Study
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Sarah Amber Evans; Lingzi Hong; Jeonghyun Kim; Erin Rice-Oyler; Irhamni Ali – Information and Learning Sciences, 2024
Purpose: Data literacy empowers college students, equipping them with essential skills necessary for their personal lives and careers in today's data-driven world. This study aims to explore how community college students evaluate their data literacy and further examine demographic and educational/career advancement disparities in their…
Descriptors: Community College Students, Self Evaluation (Individuals), Data Analysis, Demography
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Bennett L. Schwartz – Metacognition and Learning, 2024
Retrospective confidence refers to the phenomenological experience of the level of certainty that retrieved information is, in fact, correct. Retrospective confidence judgments are examined across a range of sub-disciplines in psychology from perception to memory research, and in education and legal applications. This paper focuses on…
Descriptors: Memory, Recall (Psychology), Cues, Learning Processes
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Zhifang Tu; Jiashu Shen – Research Evaluation, 2024
The economic significance of open research data is widely acknowledged, yet its quantification remains challenging. This paper presents an effective valuation instrument to help stakeholders understand and evaluate the economic benefits of open research data. By conducting a scoping review and prioritizing user engagement, this study introduces a…
Descriptors: Open Education, Economics, Data, Access to Information
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Maxi Schulz; Malte Kramer; Oliver Kuss; Tim Mathes – Research Synthesis Methods, 2024
In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…
Descriptors: Meta Analysis, Data Analysis, Research Methodology, Research Problems
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