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Chia-Yu Hsu; Izumi Horikoshi; Rwitajit Majumdar; Hiroaki Ogata – Educational Technology & Society, 2024
This study focuses on the problem that the process of building learning habits has not been clearly described. Therefore, we aim to extract the stages of learning habits from log data. We propose a data model to extract stages of learning habits based on the transtheoretical model and apply the model to the learning logs of self-directed extensive…
Descriptors: Habit Formation, Behavior Change, Learning Analytics, Data Interpretation
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Rwitajit Majumdar; Huiyong Li; Yuanyuan Yang; Hiroaki Ogata – Educational Technology & Society, 2024
Self-direction skill (SDS) is an essential 21st-century skill that can help learners be independent and organized in their quest for knowledge acquisition. While some studies considered learners from higher education levels as the target audience, providing opportunities to start the SDS practice by K12 learners is still rare. Further, practicing…
Descriptors: 21st Century Skills, Skill Development, Electronic Learning, Physical Activity Level
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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
Stradtmann, Amy A. – ProQuest LLC, 2023
Motivation and engagement are often barriers to literacy for adolescent readers. Traditionally, the graphic novel has been seen as easy to read and a resource that only has value for students with language difficulties or learning challenges. This qualitative case study investigated how middle school readers' ability to make meaning contributed to…
Descriptors: Middle School Students, Reading Motivation, Learner Engagement, Reading
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Sorensen, Lucy C. – Educational Administration Quarterly, 2019
Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…
Descriptors: At Risk Students, Dropouts, Data Collection, Data Analysis
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Dow, Mirah J.; McMahon-Lakin, Jacqueline – School Library Research, 2012
To address the presence or absence of school librarians in Kansas public schools, a study using analysis of covariance (ANCOVA) was designed to investigate staffing levels for library media specialists (LMSs), the label used for school librarians in licensed-personnel data in Kansas, and student achievement at the school level. Five subject areas…
Descriptors: School Libraries, Librarians, Personnel Data, Academic Achievement
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Rubenstein, Rheta N.; Thompson, Denisse R. – Mathematics Teaching in the Middle School, 2012
Mathematics is rich in visual representations. Such visual representations are the means by which mathematical patterns "are recorded and analyzed." With respect to "vocabulary" and "symbols," numerous educators have focused on issues inherent in the language of mathematics that influence students' success with mathematics communication.…
Descriptors: Student Attitudes, Symbols (Mathematics), Mathematics Instruction, Visual Stimuli
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National Center for Education Statistics, 2011
Representative samples of fourth- and eighth-grade public school students from 21 urban districts participated in the 2011 National Assessment of Educational Progress (NAEP) in reading. Eighteen of the districts participating in the 2011 NAEP Trial Urban District Assessment (TUDA) participated in earlier assessment years, while three districts…
Descriptors: Achievement Gap, Comparative Analysis, Disabilities, Educational Assessment