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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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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
Sauder, Adrienne E.; Gilson, Cindy M. – Gifted Child Quarterly, 2023
There is a growing body of literature around digital research, specifically regarding data collection and how to pivot research designs to be more conducive to online and virtual research, but little in the way of how to analyze data remotely. In this article, we share firsthand experiences from a qualitative study utilizing Google apps, Zoom, and…
Descriptors: Academically Gifted, Gifted Education, Qualitative Research, Data Collection
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
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Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
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Mettis, Kadri; Väljataga, Terje – International Journal of Mobile and Blended Learning, 2022
The aim of this study was to investigate how mobile outdoor learning supports the development of students' conceptual understanding about local socio-environmental problems and students' attitudes towards the learning activity. To explore these aspects, a study following a design-based research model was designed and conducted with 68 eighth-ninth…
Descriptors: Middle School Students, Outdoor Education, Environmental Education, Social Problems
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Bryan, Leah N.; Brener, Nancy; Barker, Lawrence; Lo, Annie; Underwood, J. Michael – Health Education Journal, 2021
Objective: After the discontinuation of School Health Policies and Practices Study (SHPPS) in 2016, the US Centers for Disease Control and Prevention (CDC) began exploring innovative ways to gather school health information using existing surveillance systems. School Health Profiles (Profiles) is a school-based system of surveys that monitors…
Descriptors: School Policy, School Health Services, State Agencies, Data Collection
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Oliveira, António; Ribeiro, Fabiana Silva; Ribeiro, Luísa Mota; McPherson, Gary; Oliveira-Silva, Patrícia – Music Education Research, 2021
Motivation is a crucial aspect of learning, particularly in the field of music. For decades, motivation for learning music has been a much-discussed subject, and yet its influence still remains a convoluted issue. This study systematically analyses peer-reviewed English language studies, according to PRISMA guidelines, in order to understand how…
Descriptors: Learning Motivation, Music Education, Musical Instruments, Educational Research
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Pearce, Erin; Brock, Jesse; Bunch, Phillis – Journal of Educational Research and Practice, 2022
Pre-service teachers (PSTs) often lack the self-efficacy necessary to effectively implement STEM education into their classrooms. Undergraduate research experiences (URE) can help fill this void by providing opportunities for PSTs to engage with STEM content and K-12 students in a field-based research context. This case study details the impact a…
Descriptors: Preservice Teachers, Student Attitudes, Self Efficacy, STEM Education
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Haara, Frode Olav – European Journal of Science and Mathematics Education, 2022
This article reports on how a pedagogical entrepreneurship approach combined with fundamental elements of mathematical modelling may be used to strengthen students' development of mathematical literacy in upper primary school. This is done first through a review of the relationship between pedagogical entrepreneurship in mathematics, mathematical…
Descriptors: Mathematical Models, Entrepreneurship, Mathematics Instruction, Knowledge Level
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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
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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Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
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Hardy, Lisa; Dixon, Colin; Hsi, Sherry – Journal of the Learning Sciences, 2020
This paper contributes a theoretical framework informed by historical, philosophical and ethnographic studies of science practice to argue that data should be considered to be actively produced, rather than passively collected. We further argue that traditional school science laboratory investigations misconstrue the nature of data and overly…
Descriptors: Data Collection, Data Analysis, Science Instruction, Grade 9
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Verlenden, Jorge; Naser, Shereen; Brown, Jeffrey – Journal of Applied School Psychology, 2021
Behavioral and social-emotional challenges experienced in childhood are risk factors for negative educational and health outcomes. Universal social-emotional screening in schools has been identified as an effective approach to identifying children at risk for mental health and behavioral challenges and is congruent with tiered frameworks for…
Descriptors: Screening Tests, Behavior Problems, Emotional Problems, At Risk Persons
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