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Toshiya Arakawa; Haruki Miyakawa – Technology, Knowledge and Learning, 2025
Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…
Descriptors: Data Science, Educational Games, Statistics Education, Foreign Countries
Bret Bailey – ProQuest LLC, 2024
The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…
Descriptors: Academic Achievement, Grade 6, Data, Mathematics
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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
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Mihyun Son; Minsu Ha – Education and Information Technologies, 2025
Digital literacy is essential for scientific literacy in a digital world. Although the NGSS Practices include many activities that require digital literacy, most studies have examined digital literacy from a generic perspective rather than a curricular context. This study aimed to develop a self-report tool to measure elements of digital literacy…
Descriptors: Test Construction, Measures (Individuals), Digital Literacy, Scientific Literacy
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Li, Xiaoyu; Xia, Jianping – Science Insights Education Frontiers, 2020
The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…
Descriptors: Foreign Countries, Middle School Students, Data Analysis, Data Collection
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Zhu, Mengxiao; Zhang, Mo; Deane, Paul – ETS Research Report Series, 2019
The research on using event logs and item response time to study test-taking processes is rapidly growing in the field of educational measurement. In this study, we analyzed the keystroke logs collected from 761 middle school students in the United States as they completed a persuasive writing task. Seven variables were extracted from the…
Descriptors: Keyboarding (Data Entry), Data Collection, Data Analysis, Writing Processes
Schweig, Jonathan; McEachin, Andrew; Kuhfeld, Megan; Mariano, Louis T.; Diliberti, Melissa Kay – RAND Corporation, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Jonathan Schweig; Andrew McEachin; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
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Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
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Guo, Hongwen; Zhang, Mo; Deane, Paul; Bennett, Randy E. – Journal of Educational Data Mining, 2020
This study investigates the effects of a scenario-based assessment design on students' writing processes. An experimental data set consisting of four design conditions was used in which the number of scenarios (one or two) and the placement of the essay task with respect to the lead-in tasks (first vs. last) were varied. Students' writing…
Descriptors: Instructional Effectiveness, Vignettes, Writing Processes, Learning Analytics
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Gao, Niu; Semykina, Anastasia – Journal of Research on Educational Effectiveness, 2021
Inappropriate treatment of missing data may introduce bias into the value-added estimation. We consider a commonly used value-added model (VAM), which includes the past student test score as a covariate. We formulate a joint model of student achievement and missing data, in which the probability of observing a test score depends on observing the…
Descriptors: Value Added Models, Elementary School Teachers, Computation, Scores
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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
Krystal F. Lassiter – ProQuest LLC, 2021
The purpose of this quantitative predictive analysis study was to identity what student characteristics such as subgroups' gender, ELL, race/ethnicity, more specifically Black and Latino, are important in predicting student achievement in two Priority schools in their final year of Regional Achievement Center (RAC) delivery and support to these…
Descriptors: Middle School Students, Academic Achievement, Regional Characteristics, Educational Development
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Clark, Amy; Kobrin, Jennifer L.; Karvonen, Meagan; Hirt, Ashley – Practical Assessment, Research & Evaluation, 2023
Large-scale summative assessment results are typically used for program-evaluation and resource-allocation purposes; however, stakeholders increasingly desire results from large-scale K-12 assessments that inform instruction. Because large-scale summative results are usually delivered after the end of the school year, teacher use of results is…
Descriptors: Data Use, Diagnostic Tests, Decision Making, Summative Evaluation
La Salle, Tamika P. – Center on Positive Behavioral Interventions and Supports, 2020
The purpose of this brief is to provide information about how to evaluate school climate at the primary and secondary levels. Norms and ranges are provided and based on a national data; this data can help schools to contextualize local data. Information for interpreting the data and unit if for data-based decision making is also included.
Descriptors: School Surveys, Educational Environment, Student Surveys, Student Characteristics
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