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Jennifer L. Chiu; James P. Bywater; Tugba Karabiyik; Alejandra Magana; Corey Schimpf; Ying Ying Seah – Journal of Science Education and Technology, 2024
Despite an increasing focus on integrating engineering design in K-12 settings, relatively few studies have investigated how to support students to engage in systematic processes to optimize the designs of their solutions. Emerging learning technologies such as computational models and simulations enable rapid feedback to learners about their…
Descriptors: Engineering, Middle School Students, High School Students, Building Design
Cohausz, Lea; Tschalzev, Andrej; Bartelt, Christian; Stuckenschmidt, Heiner – International Educational Data Mining Society, 2023
Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…
Descriptors: Information Retrieval, Data Processing, Pattern Recognition, Information Technology
Christine G. Casey, Editor – Centers for Disease Control and Prevention, 2024
The "Morbidity and Mortality Weekly Report" ("MMWR") series of publications is published by the Office of Science, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Articles included in this supplement are: (1) Overview and Methods for the Youth Risk Behavior Surveillance System --…
Descriptors: High School Students, At Risk Students, Health Behavior, National Surveys
Bondaryk, Leslie G.; Hsi, Sherry; Van Doren, Seth – IEEE Transactions on Learning Technologies, 2021
Sensor systems have the potential to make abstract science phenomena concrete for K-12 students. Internet of Things (IoT) sensor systems provide a variety of benefits for modern classrooms, creating the opportunity for global data production, orienting learners to the opportunities and drawbacks of distributed sensor and control systems, and…
Descriptors: Internet, Systems Development, Computer Uses in Education, Secondary School Science
Pangrazio, Luci; Selwyn, Neil – Pedagogy, Culture and Society, 2021
The ongoing 'datafication' of contemporary society has a number of implications for schools and schooling. One is the increasing calls for schools to help develop young people's understandings about the role that digital data now plays in their everyday lives -- especially in terms of the 'data economy' and 'surveillance capitalism'. Reporting on…
Descriptors: Data Collection, Data Analysis, Technology Uses in Education, Data Processing
Duprey, Michael A.; Pratt, Daniel J.; Wilson, David H.; Jewell, Donna M.; Brown, Derick S.; Caves, Lesa R.; Kinney, Satkartar K.; Mattox, Tiffany L.; Ritchie, Nichole Smith; Rogers, James E.; Spagnardi, Colleen M.; Wescott, Jamie D. – National Center for Education Statistics, 2020
This data file documentation accompanies new data files for the High School Longitudinal Study of 2009 (HSLS:09) Postsecondary Education Transcript Study and Student Financial Aid Records Collection (PETS-SR). HSLS:09 follows a nationally representative sample of students who were ninth-graders in fall 2009 from high school into postsecondary…
Descriptors: Longitudinal Studies, High School Students, Sampling, Data Collection
P. Janelle McFeetors – Sage Research Methods Cases, 2016
This case study describes an experience of using constructivist grounded theory to analyze data. The project investigated how high school students improved their approaches to learning mathematics. Over 4 months, students participated in processes which supported their learning while simultaneously generating data, including interactive writing,…
Descriptors: High School Students, Mathematics Education, Data Analysis, Data Interpretation
Liu, Ran; Stamper, John; Davenport, Jodi – Grantee Submission, 2018
Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Learning, Data Analysis, Student Development
Ingels, Steven J.; Pratt, Daniel J.; Jewell, Donna M.; Mattox, Tiffany; Dalton, Ben; Rosen, Jeffrey; Lauff, Erich; Hill, Jason – National Center for Education Statistics, 2012
This report describes the methodologies and results of the third follow-up Education Longitudinal Study of 2002 (ELS:2002/12) field test which was conducted in the summer of 2011. The field test report is divided into six chapters: (1) Introduction; (2) Field Test Survey Design and Preparation; (3) Data Collection Procedures and Results; (4) Field…
Descriptors: Longitudinal Studies, Field Tests, Followup Studies, Surveys
Levy, Sharona T.; Wilensky, Uri – Computers & Education, 2011
This study lies at an intersection between advancing educational data mining methods for detecting students' knowledge-in-action and the broader question of how conceptual and mathematical forms of knowing interact in exploring complex chemical systems. More specifically, it investigates students' inquiry actions in three computer-based models of…
Descriptors: Test Content, Mathematical Models, Prior Learning, Data Processing
Lin, Fu-Ren; Hsieh, Lu-Shih; Chuang, Fu-Tai – Computers & Education, 2009
As course management systems (CMS) gain popularity in facilitating teaching. A forum is a key component to facilitate the interactions among students and teachers. Content analysis is the most popular way to study a discussion forum. But content analysis is a human labor intensity process; for example, the coding process relies heavily on manual…
Descriptors: Secondary School Science, Online Courses, Earth Science, Classification
Ingels, Steven J.; Pratt, Daniel J.; Rogers, James E.; Siegel, Peter H.; Stutts, Ellen S. – National Center for Education Statistics, 2005
This report provides guidance and documentation for users of the public release for the combined base-year and first follow-up data of the Education Longitudinal Study of 2002 (ELS:2002). It provides extensive documentation of the content of the data files and how to access and manipulate them. Chapter 1 serves as an introduction to ELS:2002. It…
Descriptors: Guides, Data Processing, Data Collection, Longitudinal Studies
Ingels, Steven J.; Pratt, Daniel J.; Wilson, David; Burns, Laura J.; Currivan, Douglas; Rogers, James E.; Hubbard-Bednasz, Sherry – National Center for Education Statistics, 2007
This manual has been produced to familiarize data users with the procedures followed for data collection and processing for the base year through second follow-up of the Education Longitudinal Study of 2002 (ELS:2002). It also provides the necessary documentation for use of the data files, as they appear on the ELS:2002 base-year to second…
Descriptors: Longitudinal Studies, High School Students, Research Design, Data Collection
Klein, Joseph; Weiss, Itzhak – Journal of Educational Administration, 2007
Purpose: The literature advocates educational decision-making processes that are either intuitive or systematic. While the two approaches seem to be incompatible, each has its merits. Intuitive thinking is considered to be holistic and creative, whereas the systematic approach has the advantages of a theoretical foundation and accuracy in data…
Descriptors: Decision Making, Data Processing, Teaching Methods, Thinking Skills
Riccobono, John; Henderson, Louise B.; Burkheimer, Graham J.; Place, Carol; Levinsohn, Jay R. – National Center for Education Statistics, 1981
The National Longitudinal Study (NLS) of the High School Class of 1972 is a large-scale long-term survey effort supported by the National Center for Education Statistics (NCES), Office of the Assistant Secretary for Educational Research and Improvement in the U.S. Department of Education. NLS is designed to provide statistics on a national sample…
Descriptors: Longitudinal Studies, National Surveys, Followup Studies, High School Graduates

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