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Wayne Nirode – Mathematics Teacher: Learning and Teaching PK-12, 2025
This article details an exploratory data analysis project using the Common Online Data Analysis Platform (CODAP) based on the "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) four-part statistical problem-solving model. The project goal was to answer what similarities and differences exist within the school…
Descriptors: Data Analysis, Problem Solving, Models, Common Core State Standards
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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
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Haynes-Brown, Tashane K. – Journal of Mixed Methods Research, 2023
The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the…
Descriptors: Theories, Models, Mixed Methods Research, Teacher Attitudes
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Jiawei Xiong; George Engelhard; Allan S. Cohen – Measurement: Interdisciplinary Research and Perspectives, 2025
It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…
Descriptors: Responses, Test Items, Test Format, Grade 8
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
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Zorluoglu, Seraceddin Levent; Yalçinkaya Önder, Eylem; Timur, Betül; Timur, Serkan; Güvenç, Elif; Özergun, Ilgim; Özdemir, Muzaffer – Journal of Baltic Science Education, 2022
Science education focuses on the methods of thinking about and using process skills rather than memorizing scientific facts. 5E educational model aims to learn by discovering scientific knowledge and engaging students in learning environments. The aim of this study was to examine the articles in the field of education related to the 5E educational…
Descriptors: Science Process Skills, Models, Science Instruction, Teaching Methods
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Iurasov, Aleksei – International Journal of Learning and Change, 2022
Students who have graduated from high schools across the EU member states can choose from a wide variety of study programs and universities at which to pursue their degree studies. Each combination of a university and study program is unique, which further complicates student choice. Lack of information transparency regarding the unique…
Descriptors: Foreign Countries, Information Technology, Business Administration Education, Undergraduate Study
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Jiang, Shiyan; Qian, Yingxiao; Tang, Hengtao; Yalcinkaya, Rabia; Rosé, Carolyn P.; Chao, Jie; Finzer, William – Education and Information Technologies, 2023
As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Artificial Intelligence
Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…
Descriptors: Intervention, Outcomes of Education, Randomized Controlled Trials, Data Use
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Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – International Educational Data Mining Society, 2024
The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…
Descriptors: Intervention, Outcomes of Education, Randomized Controlled Trials, Data Use
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Gaoxia Zhu; Chew Lee Teo; Aloysius Kian-Keong Ong; Katherine Guangji Yuan; Chin Lee Ker; Yuqin Yang – Education and Information Technologies, 2025
Preparing the new generation to be data-literate citizens is a pressing challenge, and some explorations have been made to cultivate K-12 students' data science skills and attitudes. However, there is a lack of instructional models to guide the design of data science programs in K-12 due to its complex and interdisciplinary nature as well as the…
Descriptors: Data Science, Skill Development, Secondary School Students, Cooperative Learning
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Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
Erin W. Post – ProQuest LLC, 2024
Multivariate count data is ubiquitous in many areas of research including the physical, biological, and social sciences. These data are traditionally modeled with the Dirichlet Multinomial distribution (DM). A new, more flexible Dirichlet-Tree Multinomial (DTM) model is gaining in popularity. Here, we consider Bayesian DTM regression models. Our…
Descriptors: Regression (Statistics), Multivariate Analysis, Statistical Distributions, Bayesian Statistics
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Nurullah Eryilmaz; Andres Sandoval Hernandez – Educational Studies, 2024
Recently, there has been increasing interest in comparing educational leadership measures, such as principal school leadership, using International Large-Scale Assessments (ILSAs) data. However, there are doubts about the uniformity of measurement across countries participating in the ILSAs. There are concerns that the robustness and psychometric…
Descriptors: Instructional Leadership, School Administration, Global Approach, Models
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Prieto, Luis P.; Magnuson, Paul; Dillenbourg, Pierre; Saar, Merike – Technology, Pedagogy and Education, 2020
Improving educational practice through reflection is one important focus of teacher professional development approaches. However, such teacher reflection operates under practical classroom constraints that make it happen infrequently, including the reliance on disruptive peer/supervisor observations or recordings. This article describes three…
Descriptors: Faculty Development, Reflection, Secondary School Teachers, Educational Technology
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