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Emil Smith; David Reimer – Child Development, 2024
This study examined gender differences in reading behavior of 2652 Danish 5th-grade students (age 10-12 years, girls 51%, 14% immigrant background) observed for 218 days in 2019/2020, using data from a popular reading app. Reading behavior was operationalized as time spent reading. Analyses of timing of reading behavior and models of day-to-day…
Descriptors: Foreign Countries, Gender Differences, Grade 5, Reading Habits
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Felix Bittmann – Reading Research Quarterly, 2025
Do children with better reading competence read more, or do avid readers increase their reading competence? This highly relevant question has been discussed for many years, yet conclusive results are rare. Previous studies suffer from small sample sizes or omitted variable bias, rendering their findings questionable. We provide new insight using…
Descriptors: Reading, Opportunities, Reading Instruction, Gender Differences
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Tugba Pürsün – Journal of Educational Research, 2024
In this study, structural equation modeling was used to examine the effect of gifted students' attitudes toward reading on their reading habits and writing tendencies. The study group for this research, in which the correlational survey model was used, was formed with the convenience sampling method. The study was conducted with 134 gifted…
Descriptors: Foreign Countries, Academically Gifted, Reading Attitudes, Reading Habits
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Amanda Yoshiko Shimizu; Michael Havazelet; Amanda P. Goodwin – AERA Open, 2024
Digital reading is ubiquitous, yet understanding digital reading processes and links to comprehension remains underdeveloped. Guided by new literacies and active reading theories, this study explored the reading behaviors and comprehension of thirteen fifth graders who read static digital texts. We coded for the quantity and quality of digital…
Descriptors: Elementary School Students, Grade 5, Reading Comprehension, Reading Processes
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Munise Seçkin Kapucu; I?brahim Özcan; Hülya Özcan; Ahmet Aypay – International Journal of Technology in Education and Science, 2024
Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…
Descriptors: Secondary School Students, Science Achievement, Artificial Intelligence, Foreign Countries