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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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Ulitzsch, Esther; Lüdtke, Oliver; Robitzsch, Alexander – Educational Measurement: Issues and Practice, 2023
Country differences in response styles (RS) may jeopardize cross-country comparability of Likert-type scales. When adjusting for rather than investigating RS is the primary goal, it seems advantageous to impose minimal assumptions on RS structures and leverage information from multiple scales for RS measurement. Using PISA 2015 background…
Descriptors: Response Style (Tests), Comparative Analysis, Achievement Tests, Foreign Countries
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Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2020
Peter Dunn and Margaret Marshman present the second of their data files articles in which they discuss the statistical investigation cycle which describes the whole process of conducting a statistical research study. [For "The Data Files: A Series of Articles to Support Mathematics Teachers to Teach Statistics," see EJ1259108.]
Descriptors: Statistics, Data Analysis, Teaching Methods, Problem Solving
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Bryan, Leah N.; Smith-Grant, Jennifer; Brener, Nancy; Kilmer, Greta; Lo, Annie; Queen, Barbara; Underwood, J. Michael – Journal of School Health, 2022
Background: Since the inception of the Youth Risk Behavior Surveillance System in 1991, all surveys have been conducted in schools, using paper and pencil instruments (PAPI). For the 2019 YRBSS, sites were offered the opportunity to conduct their surveys using electronic data collection. This study aimed to determine whether differences in select…
Descriptors: Risk, Health Behavior, Incidence, Adolescents
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Karel Kok; Burkhard Priemer – Physical Review Physics Education Research, 2023
Students at all levels of education experience difficulties with the concepts of measurement uncertainties. One task that includes concepts of measurement uncertainties is a data comparison problem where students decide whether two datasets are in agreement or not--an authentic scientific practice. To aid students with these concepts and tasks,…
Descriptors: Data Analysis, Comparative Analysis, Secondary School Students, Teaching Methods
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Hung, Jeng-Fung; Tsai, Chun-Yen – Journal of Baltic Science Education, 2020
Previous studies on the effectiveness of virtual laboratories for learning have shown inconsistent results over the past decade. The purpose of this research was to explore the effects of a virtual laboratory and meta-cognitive scaffolding on students' data modeling competences. A quasi-experimental design was used. Three classes of eighth graders…
Descriptors: Metacognition, Computer Simulation, Comparative Analysis, Science Laboratories
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Kim, Jonghun – Educational Philosophy and Theory, 2022
This study examines the Programme for International Student Assessment (PISA), one of the most influential tools of global education reform discourses in the 21st century. The study focuses on the governing role of statistical data in the discourse constructed by the international comparative assessment, referring to the global educational…
Descriptors: Statistical Data, Governance, Academic Achievement, Accountability
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Larry J. Grabau; Jan Van Damme – International Journal of Science and Mathematics Education, 2024
Adaptive science dispositions (epistemology, enjoyment, interest, and self-efficacy) have been shown to be related to schools' science climate and science literacy. School stratification may promote positive linkages among science dispositions, science literacy, and science climate. To examine the association between school stratification and such…
Descriptors: Foreign Countries, Scientific Literacy, Educational Environment, Science Education
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Dong, Fang; Kula, Maria Cornachione – Education Economics, 2023
This paper uses data from the OECD's 2015 PISA and an endogenous treatment effects model to investigate the impact of different intensities of digital device use for academic purposes on science learning outcomes. When we do not differentiate the location of device use, we find that greater use can help students improve their science scores in…
Descriptors: Technology Uses in Education, Scientific Literacy, Achievement Tests, Foreign Countries
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Xue, Xiaorui; Xie, Shiwei; Mishra, Shitanshu; Wright, Anna M.; Biswas, Gautam; Levin, Daniel T. – Educational Technology Research and Development, 2022
Recent advances in eye-tracking technology afford the possibility to collect rich data on attentional focus in a wide variety of settings outside the lab. However, apart from anecdotal reports, it is not clear how to maximize the validity of these data and prevent data loss from tracking failures. Particularly helpful in developing these…
Descriptors: Case Studies, Eye Movements, Comparative Analysis, Human Posture
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Klingbeil, David A.; Osman, David J.; Van Norman, Ethan R.; Berry-Corie, Kimberly; Kim, Jessica S.; Schmitt, Madeline C.; Latham, Alexander D. – Reading & Writing Quarterly, 2023
Accurate and efficient universal screening is a foundational component of multi-tiered systems of support for reading. By the time students reach middle school, educators often have extant data available to inform screening decisions. Therefore, the decision to collect additional data to inform screening should be considered carefully. The…
Descriptors: Screening Tests, Reading Tests, Middle School Students, Identification
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Göktepe Körpeoglu, Seda; Göktepe Yildiz, Sevda – Education and Information Technologies, 2023
Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…
Descriptors: Comparative Analysis, Algorithms, Data Collection, Student Attitudes
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Xue Wang – Society for Research on Educational Effectiveness, 2024
Inequality in the shadow? Cross-national comparisons of the effects of additional instruction on math and science performance based on PISA 2018 data Background Many educational systems worldwide are experiencing a growing demand for shadow education, which often takes the form of outside-school educational activities such as private tutoring…
Descriptors: Equal Education, Comparative Analysis, Supplementary Education, International Assessment
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Eva Ponte – Center for Educational Policy Studies Journal, 2024
Education is seen as a resource at a global level but is currently considered to be in crisis in many parts of the world. This constitutes a significant drawback in terms of humanity's prosperity and well-being since education is the key not only to an educated workforce but also to humane, collaborative, and caring societies. Even within this dim…
Descriptors: Foreign Countries, Grade 8, Grade 4, Mathematics Education
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