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Shaun Bhatia; Leonard A. Jason – Journal of Disability Policy Studies, 2024
There have been numerous iterations of naming convention specified for myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS). As health care turns to "big data" analytics to gain insights, the Google Trends database was mined to ascertain worldwide trends of public interest in several ME- and CFS-related search categories…
Descriptors: Data Analysis, Chronic Illness, Search Strategies, Information Retrieval
Stephanie Wermelinger; Marco Bleiker; Moritz M. Daum – Infant and Child Development, 2025
Children's fuzziness leads to increased variance in the data, data loss, and high dropout rates in developmental studies. This study investigated the importance of 20 factors on the person (child, caregiver, experimenter) and situation (task, method, time, and date) level for the data quality as indicated via the number of valid trials in 11…
Descriptors: Infants, Young Children, Research Problems, Factor Analysis
Axel Langner; Lea Sophie Hain; Nicole Graulich – Journal of Chemical Education, 2025
Often, eye-tracking researchers define areas of interest (AOIs) to analyze eye-tracking data. Although AOIs can be defined with systematic methods, researchers in organic chemistry education eye-tracking research often define them manually, as the semantic composition of the stimulus must be considered. Still, defining appropriate AOIs during data…
Descriptors: Organic Chemistry, Science Education, Eye Movements, Educational Research
Safa Ridha Albo Abdullah; Ahmed Al-Azawei – International Review of Research in Open and Distributed Learning, 2025
This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…
Descriptors: Electronic Learning, Academic Achievement, Grade Prediction, Data Analysis
Flavio Manganello; Chiara Fante – Journal of Learning Analytics, 2025
Learning Analytics (LA) is increasingly applied to assess and foster creativity in educational settings. Whereas existing applications have shown promise in STEM contexts, less is known about the diversity of approaches across educational domains. Therefore, we conducted a scoping review that systematically mapped LA applications for creativity in…
Descriptors: Literature Reviews, Creativity, Context Effect, Learning Analytics
Buckner, Elizabeth; Shephard, Daniel; Smiley, Anne – Journal on Education in Emergencies, 2022
Recognizing the lack of knowledge about how to improve data systems for education in emergencies (EiE), we examine in this article how EiE professionals use data and what makes data "useful" to them. Drawing from 48 semistructured interviews from a purposive sample of professionals working in the EiE field across the humanitarian,…
Descriptors: Data Use, Emergency Programs, Professional Personnel, Attitudes
Viberg, Olga; Mutimukwe, Chantal; Grönlund, Åke – Journal of Learning Analytics, 2022
Protection of student privacy is critical for scaling up the use of learning analytics (LA) in education. Poorly implemented frameworks for privacy protection may negatively impact LA outcomes and undermine trust in the discipline. To design and implement models and tools for privacy protection, we need to understand privacy itself. To develop…
Descriptors: Privacy, Learning Analytics, Educational Research, Definitions
Swenson, Sandra; He, Yi; Boyd, Heather; Good, Kate Schowe – Journal of College Science Teaching, 2022
Students reasoning with data in an authentic science environment had the opportunity to learn about the process of science and the world around them while developing skills to analyze and interpret self-collected and secondhand data. Our results show that nearly 50% of the treatment group responses were accurate when describing the reason for…
Descriptors: Design, Heuristics, Data Analysis, Data Interpretation
Watkins, Karen E.; Ellinger, Andrea D.; Suh, Boyung; Brenes-Dawsey, Joseph C.; Oliver, Lisa C. – European Journal of Training and Development, 2022
Purpose: The critical incident technique (CIT) is widely used in many disciplines; however, scholars have acknowledged challenges associated with analyzing qualitative data when using this technique. Therefore, the purpose of this article is to address the data analysis issues that have been raised by introducing some different contemporary ways…
Descriptors: Critical Incidents Method, Data Analysis, Doctoral Dissertations, Labor Force Development
Mertala, Pekka – Journal of Media Literacy Education, 2020
This position paper uses the concept of "hidden curriculum" as a heuristic device to analyze everyday data-related practices in formal education. Grounded in a careful reading of the theoretical literature, this paper argues that the everyday data-related practices of contemporary education can be approached as functional forms of data…
Descriptors: Data, Multiple Literacies, Hidden Curriculum, Information Sources
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
Usova, Tatiana; Laws, Robert – Journal of Information Literacy, 2021
Data literacy skills are becoming critical in today's world as the quantity of data grows exponentially and becomes the 'currency' of power. In spring 2020, a team of two librarians piloted a new one-credit course in data literacy and data visualisation. This report explains the rationale behind the project and discusses the place of data literacy…
Descriptors: College Credits, Information Literacy, Data, Visualization
Khulbe, Manisha; Tammets, Kairit – Technology, Knowledge and Learning, 2023
Insights derived from classroom data can help teachers improve their practice and students' learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of…
Descriptors: Faculty Development, Learning Analytics, Intervention, Teacher Attitudes
Berg, Stephanie A.; Moon, Alena – Chemistry Education Research and Practice, 2023
Both graph comprehension and data analysis and interpretation are influenced by one's prior knowledge and experiences. To understand how one's prior knowledge and experiences interact with their analysis of a graph, we conducted think-aloud interviews with general chemistry students as they interpreted a graph to determine optimal conditions for…
Descriptors: Graphs, Data Analysis, Data Interpretation, Science Process Skills
Christine Ladwig; Taylor Webber; Dana Schwieger – Information Systems Education Journal, 2023
Data is a powerful tool for the healthcare industry to use for managing, analyzing, and reporting on critical events in the field. The analysis of broad, salient data files aids healthcare businesses in uncovering hidden patterns, market trends, and customer preferences; these details may then be used to improve the quality and delivery of care to…
Descriptors: Rural Areas, Health Services, Data Analysis, Learning Activities

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