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Siobhan Reilley – Impacting Education: Journal on Transforming Professional Practice, 2024
The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…
Descriptors: Data Use, Data Collection, Data Analysis, Teacher Leadership
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Moulaison-Sandy, Heather; Wenzel, André G. – portal: Libraries and the Academy, 2023
This conceptual article considers data used in the humanities and the human sciences, which are fundamentally different from data in other disciplines, such as the sciences or medicine. Data in the humanities are, however, equally important to study and understand. Humanists and others studying human artifacts often face the dual challenge of both…
Descriptors: Data Collection, Information Management, Humanities, Data Use
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Karly B. Ball; Rachel Elizabeth Traxler – International Journal of Research & Method in Education, 2024
As Twitter's (or X's) influence permeates aspects of education, researchers must consider how to ethically and effectively leverage the unique types of data that this social media platform offers. This paper provides recommended methodological practice considerations for working with qualitative Twitter data toward the advancement of education…
Descriptors: Educational Research, Research Methodology, Social Media, Ethics
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Cintron, Dakota W.; Montrosse-Moorhead, Bianca – American Journal of Evaluation, 2022
Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim…
Descriptors: Evaluation Research, Evaluation Problems, Evaluation Methods, Models
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Pieterman-Bos, Annelies; van Mil, Marc H. W. – Science & Education, 2023
Biomedical data science education faces the challenge of preparing students for conducting rigorous research with increasingly complex and large datasets. At the same time, philosophers of science face the challenge of making their expertise accessible for scientists in such a way that it can improve everyday research practice. Here, we…
Descriptors: Philosophy, Science Education, Scientific Principles, Data Science
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Chelsea M. Parlett-Pelleriti; Elizabeth Stevens; Dennis Dixon; Erik J. Linstead – Review Journal of Autism and Developmental Disorders, 2023
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data--both genetic and behavioral--that are collected as part of scientific studies or a part of treatment can provide a deeper,…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Classification, Supervision
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Annie Irvine – International Journal of Social Research Methodology, 2024
Engaging with primary researchers during qualitative secondary analysis is a practice much recommended but rarely written about. In this article, I reflect on my experience of crossing an imagined boundary between the discrete textual dataset and its creators, of acknowledging and engaging with those researchers who invested in constructing the…
Descriptors: Researchers, Foreign Countries, Primary Sources, Research Methodology
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Samantha Fu; Charles Davis; Jesse Rothstein; Aparna Ramesh; Evan White – Grantee Submission, 2022
Linking data together can be a powerful way for governments and researchers alike to tackle vexing public policy research problems. However, for researchers, finding ways to link data directly between two departments can often be more challenging than even obtaining the data in the first place. Even when a researcher develops the necessary…
Descriptors: Data Use, Research Methodology, Researchers, Privacy
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Katherine Bui; Keith R. Berry Jr. – Journal of Research Administration, 2025
Research administrators (RA) at institutions of higher education (IHE) provide critical support to faculty throughout the lifecycle of research, which include developing research, applying to funding opportunities, managing awards through closeout, and maintaining compliance. Fulfilling these tasks requires well-developed RA processes and clear…
Descriptors: COVID-19, Pandemics, Data Collection, Data Use
Bryant, Matt – Association for Institutional Research, 2021
Survey methodology is the dominant approach among universities in the United States for reporting employment outcomes for recent graduates. However, past studies have shown that survey methodology may yield upwardly biased results, which can result in overreporting of employment rates and salary outcomes. This case study describes the development…
Descriptors: Data Collection, Data Use, Labor Force, Institutional Research
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Singh, Ajit – Journal of Learning and Teaching in Digital Age, 2021
The purpose of this paper is to analyze various dimensions for measurement of human behavior. Human behaviour is complex. Behaviors, emotions, cognitions, and attitudes can rarely be described in terms of one or two variables. It is multimodal in nature. Furthermore, the traits, modalities and dimensions cannot be measured directly, but must be…
Descriptors: Behavior, Measurement Techniques, Data Use, Data Collection
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Decuypere, Mathias – Journal of New Approaches in Educational Research, 2021
This paper offers a methodological framework to research data practices in education critically. Data practices are understood in the generic sense of the word here, i.e., as the actions, performances, and the resulting consequences, of introducing data-producing technologies in everyday educational situations. The paper first distinguishes…
Descriptors: Data, Data Use, Topology, Research Methodology
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Sales, Adam C.; Prihar, Ethan B.; Gagnon-Bartsch, Johann A.; Heffernan, Neil T. – Journal of Educational Data Mining, 2023
Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without confounding bias and exact statistical inference even in small samples. However, often experimental samples and/or treatment effects are small, A/B tests are underpowered,…
Descriptors: Data Use, Research Methodology, Randomized Controlled Trials, Educational Technology
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Jihua Dong; Yanan Zhao; Louisa Buckingham – ReCALL, 2023
This study employs a bibliometric approach to analyse common research themes, high-impact publications and research venues, identify the most recent transformative research, and map the developmental stages of data-driven learning (DDL) since its genesis. A dataset of 126 articles and 3,297 cited references (1994-2021) retrieved from the Web of…
Descriptors: Data Use, Learning, Research Methodology, Educational Research
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van Dijk, Wilhelmina; Schatschneider, Christopher; Hart, Sara A. – Journal of Learning Disabilities, 2021
The Open Science movement has gained considerable traction in the last decade. The Open Science movement tries to increase trust in research results and open the access to all elements of a research project to the public. Central to these goals, Open Science has promoted five critical tenets: Open Data, Open Analysis, Open Materials,…
Descriptors: Science Instruction, Scientific Research, Research Methodology, Access to Information
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