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Showing 1 to 15 of 19 results Save | Export
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Thompson, JaCoya; Arastoopour Irgens, Golnaz – Journal of Statistics and Data Science Education, 2022
Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…
Descriptors: Data Analysis, Middle School Students, Statistics Education, Student Centered Learning
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Buscher, Christian – Statistics Education Research Journal, 2022
Statistical literacy is a skill that will be required by all students, but only limited insights exist into how it can be developed in middle schools. Research is required that identifies design principles and provides didactic materials for developing statistical literacy in actual middle school classrooms, meaning classrooms in which statistics…
Descriptors: Statistics Education, Middle School Students, Literacy, Teaching Methods
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Rafiepour, Abolfazl; Abdolahpour, Kazem; Farsani, Danyal – Mathematics Teaching Research Journal, 2022
The main purpose of this study is to develop a conceptual understanding of the irrational number of the square root of 2 ([square root]2 ). Participants in the study were 20 ninth-grade male students. Activity Theory was used as a framework to show the development of the conceptual understanding. Since this study was conducted during the COVID-19…
Descriptors: Concept Formation, Mathematical Concepts, Mathematics Instruction, COVID-19
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Podworny, Susanne; Hüsing, Sven; Schulte, Carsten – Statistics Education Research Journal, 2022
Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…
Descriptors: Statistics Education, Programming, Programming Languages, Data Analysis
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Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
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Xing, Wanli; Li, Chenglu; Chen, Guanhua; Huang, Xudong; Chao, Jie; Massicotte, Joyce; Xie, Charles – Journal of Educational Computing Research, 2021
Integrating engineering design into K-12 curricula is increasingly important as engineering has been incorporated into many STEM education standards. However, the ill-structured and open-ended nature of engineering design makes it difficult for an instructor to keep track of the design processes of all students simultaneously and provide…
Descriptors: Engineering Education, Design, Feedback (Response), Student Evaluation
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Koparan, Timur – International Journal of Mathematical Education in Science and Technology, 2019
The Fatih Project in Turkey has improved software in mathematics teaching such as data analysis software. As a result, the need to inquire into the efficiency of computer-supported learning environments has emerged. This study aims to examine the effect of dynamic data analysis software-supported learning environments on secondary school students'…
Descriptors: Foreign Countries, Computer Software, Educational Technology, Technology Uses in Education
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Confrey, Jere; Shah, Meetal; Persson, Jennifer; Ciliano, Dagmara – North American Chapter of the International Group for the Psychology of Mathematics Education, 2019
This paper reports on a design-based implementation study of the use of a diagnostic classroom assessment tool framed on learning trajectories (LTs) for middle grades mathematics, where teachers and students are provided immediate data on students' progress along LTs. The study answers the question: "How can one characterize the challenges…
Descriptors: Middle School Students, Mathematics Instruction, Barriers, Diagnostic Tests
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Werner, Linda; McDowell, Charlie; Denner, Jill – Journal of Educational Data Mining, 2013
Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…
Descriptors: Electronic Learning, Learning Processes, Educational Research, Data Collection
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Ocumpaugh, Jaclyn; Baker, Ryan; Gowda, Sujith; Heffernan, Neil; Heffernan, Cristina – British Journal of Educational Technology, 2014
Information and communication technology (ICT)-enhanced research methods such as educational data mining (EDM) have allowed researchers to effectively model a broad range of constructs pertaining to the student, moving from traditional assessments of knowledge to assessment of engagement, meta-cognition, strategy and affect. The automated…
Descriptors: Research Methodology, Educational Research, Information Technology, Data Analysis
Scranton, Melissa Arnold – ProQuest LLC, 2013
The purpose of this study was to gain a better understanding of how students think in a technological environment. This was accomplished by exploring the differences in the thinking of students while they worked in a technological environment and comparing this to their work in a paper and pencil environment. The software program TinkerPlots:…
Descriptors: Middle School Students, Comparative Analysis, Computer Software, Data Analysis
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Mendiburo, Maria; Williams, Laura; Segedy, James; Hasselbring, Ted – Society for Research on Educational Effectiveness, 2013
In this paper, the authors explore the use of learning analytics as a method for easing the cognitive demands on teachers implementing the HALF instructional model. Learning analytics has been defined as "the measurement, collection, analysis and reporting of data about learners and their contexts for the purposes of understanding and…
Descriptors: Educational Research, Data Collection, Data Analysis, Teaching Methods
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Pai, Ping-Feng; Lyu, Yi-Jia; Wang, Yu-Min – Computers & Education, 2010
Rough set theory (RST) is an emerging technique used to deal with problems in data mining and knowledge acquisition. However, the RST approach has not been widely explored in the field of academic achievement. This investigation developed an improved RST (IMRST) model, which employs linear discriminant analysis to determine a reduct of RST, and…
Descriptors: Academic Achievement, Discriminant Analysis, Foreign Countries, Junior High School Students
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Liu, Yuan-Chen; Lee, Wan-Chun; Huang, Tzu-Hua; Hsieh, Hsiao-Mei – Turkish Online Journal of Educational Technology - TOJET, 2012
This research investigates students' performance while writing Chinese essays using an interactive online writing system. Participants include students from two seventh-grade classes of a junior high school in Taoyuan County, Taiwan. The experimental group uses the conditioned writing interactive online system, while the control group receives…
Descriptors: Foreign Countries, Writing Instruction, Control Groups, Experimental Groups
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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