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Saglamgöncü, Ahmet; Deveci, Handan – International Journal of Psychology and Educational Studies, 2022
Practice-based research is perceived as significantly important to enhance the quality of social studies education in the literature. In particular, graduate dissertations have great potential for contributing to the literature, and using research methods, and designs that improve practice is valuable in graduate-level research. This study focuses…
Descriptors: Social Studies, Masters Theses, Doctoral Dissertations, Research Design
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Swygart-Hobaugh, Mandy; Anderson, Raeda; George, Denise; Glogowski, Joel – College & Research Libraries, 2022
We present findings from an exploratory quantitative content analysis case study of 156 doctoral dissertations from Georgia State University that investigates doctoral student researchers' methodology practices (used quantitative, qualitative, or mixed methods) and data practices (used primary data, secondary data, or both). We discuss the…
Descriptors: Doctoral Dissertations, Doctoral Students, Research Methodology, Data Collection
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Korkmaz, Elif; Morali, Hasibe Sevgi – International Electronic Journal of Mathematics Education, 2022
Augmented reality (AR) helps three dimensional, virtual objects to be viewed, interactively, in a real-world setting. AR technology is used in many fields such as medicine, advertisement, military, industry, and increasingly in education. AR has an importantrole in concretizing educational platforms and achieving permanentlearning. This study aims…
Descriptors: Meta Analysis, Computer Simulation, Electronic Learning, Mathematics Education
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Leventhal, Brian C.; Gregg, Nikole; Ames, Allison J. – Measurement: Interdisciplinary Research and Perspectives, 2022
Response styles introduce construct-irrelevant variance as a result of respondents systematically responding to Likert-type items regardless of content. Methods to account for response styles through data analysis as well as approaches to mitigating the effects of response styles during data collection have been well-documented. Recent approaches…
Descriptors: Response Style (Tests), Item Response Theory, Test Items, Likert Scales
Chang, Hedy N. – Attendance Works, 2022
This brief examines how state policies and practices continue to evolve in light of the COVID-19 pandemic. It is based on data provided by 45 states plus the District of Columbia as of early May 2022. The brief updates our 2021 report, "Are Students Present and Accounted For? An Examination of State Attendance Policies During the COVID-19…
Descriptors: Attendance, State Policy, COVID-19, Pandemics
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Cox, Shawna; Gilary, Aaron; Simon, Dillon; Thomas, Teresa – National Center for Education Statistics, 2022
The National Center for Education Statistics (NCES) sponsors the National Teacher and Principal Survey (NTPS) on behalf of the U.S. Department of Education in order to collect data on public and private elementary and secondary schools in the United States. The NTPS is a large-scale, nationally representative sample survey of K-12 public and…
Descriptors: Teachers, Principals, Elementary Secondary Education, Administrators
Grantee Submission, 2022
Systems for learning and producing knowledge, such as career and technical education (CTE), often reproduce inequities unless an equity-focused lens is used when designing, implementing, and evaluating programs. This framework presents guidance for conducting CTE research with an intentional focus on equity. Developed by the CTE Research Network's…
Descriptors: Equal Education, Vocational Education, Educational Research, Program Administration
Daniel Rodriguez-Segura; Beth E. Schueler – Annenberg Institute for School Reform at Brown University, 2022
A significant share of education and development research uses data collected by workers called "enumerators." It is well-documented that "enumerator effects"--or inconsistent practices between the individual people who administer measurement tools-- can be a key source of error in survey data collection. However, it is less…
Descriptors: Data Collection, Educational Research, Research Problems, Elementary School Students
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Kontogianni, Feni; Hope, Lorraine; Taylor, Paul J.; Vrij, Aldert; Gabbert, Fiona – Applied Cognitive Psychology, 2020
In information gathering interviews, follow-up questions are asked to clarify and extend initial witness accounts. Across two experiments, we examined the efficacy of open-ended questions following an account about a multi-perpetrator event. In Experiment 1, 50 mock-witnesses used the timeline technique or a free recall format to provide an…
Descriptors: Data Collection, Interviews, Questioning Techniques, Identification
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Williams, Peter – European Journal of Special Needs Education, 2020
Inclusive research with people with learning disabilities often involves audio-recording interviews. However, although barely acknowledged in the literature, participants may not understand that every word recorded will be scrutinised forensically, from which possibly erroneous conclusions may be drawn. This paper describes an alternative method:…
Descriptors: Participatory Research, Inclusion, Learning Disabilities, Data Collection
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Jiang, Shiyan; Kahn, Jennifer – International Journal of Computer-Supported Collaborative Learning, 2020
Data visualization technologies are powerful tools for telling evidence-based narratives about oneself and the world. This paper contributes to the literature on data science education by examining the sociotechnical practices of data wrangling--strategies for selecting and managing large, aggregated datasets to produce a model and story. We…
Descriptors: Data Collection, Data Analysis, Visualization, Story Telling
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Wilkerson, Michelle Hoda; Polman, Joseph L. – Journal of the Learning Sciences, 2020
The emerging field of Data Science has had a large impact on science and society. This has led to over a decade of calls to establish a corresponding field of Data Science Education. There is still a need, however, to more deeply conceptualize what a field of Data Science Education might entail in terms of scope, responsibility, and execution.…
Descriptors: Data, Information Science Education, Learning, Data Collection
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François, Karen; Monteiro, Carlos; Allo, Patrick – Statistics Education Research Journal, 2020
In the contemporary society a massive amount of data is generated continuously by various means, and they are called Big-Data sets. Big Data has potential and limits which need to be understood by statisticians and statistics consumers, therefore it is a challenge to develop Big-Data Literacy to support the needs of constructive, concerned, and…
Descriptors: Data Collection, Data Analysis, Statistical Analysis, Comprehension
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Burgos, Daniel, Ed. – Lecture Notes in Educational Technology, 2020
Learning Analytics become the key for Personalised Learning and Teaching thanks to the storage, categorisation and smart retrieval of Big Data. Thousands of user data can be tracked online via Learning Management Systems, instant messaging channels, social networks and other ways of communication. Always with the explicit authorisation from the…
Descriptors: Learning Analytics, Individualized Instruction, Integrated Learning Systems, Data Collection
Díaz, Victoria E.; McKeown, Stephanie; Peña, Camilo – British Columbia Council on Admissions and Transfer, 2023
This project reviews data collection practices regarding race, ethnicity and ancestry (REA) in post-secondary institutions (PSIs) in Canada, as well as in other relevant sectors (e.g., health, K-12 education, government agencies). The goal of the project was to identify promising practices and to develop recommendations to guide REA data…
Descriptors: Data Collection, Data Use, Student Characteristics, Race
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