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Stephen L. Morgan; Jiwon Lee – Sociological Methods & Research, 2024
The linear dependence of age, period, and birth cohort is a challenge for the analysis of social change. With either repeated cross-sectional data or conventional panel data, raw change cannot be decomposed into over-time differences that are attributable to the effects of common experiences of alternative birth cohorts, features of the periods…
Descriptors: Surveys, Cohort Analysis, Data Interpretation, Observation
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Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
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Lubna Al-Gailani; Ali Al-Kaleel; Sevda Lafci Fahrioglu – Advances in Physiology Education, 2025
Due to regulatory and logistical challenges, traditional hands-on endocrine labs can be difficult to implement. Here, we provide a flexible, dry-lab/classroom data analysis activity that eliminates the need for direct blood sampling and instead focuses on teaching analytical skills and theoretical knowledge. This article presents a…
Descriptors: Metabolism, Nutrition, Dietetics, Medical Education
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Lewis, Heather H. J.; Radley, Keith C.; Dart, Evan H. – Psychology in the Schools, 2022
Single-case design (SCD) is frequently utilized in applied contexts, such as schools or clinics, due to its utility in evaluating individual intervention effects of students. Data collected in SCD are often displayed in a linear graph, which can vary drastically in their construction leading to inconsistencies in rater interpretation. This has led…
Descriptors: Graphs, Standards, School Psychologists, Differences
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Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
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Jennings, Austin S. – Elementary School Journal, 2023
Teachers' data literacy and interpretive process are critical to understanding how they make sense of data. However, little is known about how mental representations shape and evolve in response to teachers' interpretive process. In the present study, I model and explore this recursive relationship between teachers' cognitive framing and…
Descriptors: Data Interpretation, Cognitive Processes, Academic Achievement, Student Evaluation
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Soto, Alexis; Schoenlein, Melissa A.; Schloss, Karen B. – Cognitive Research: Principles and Implications, 2023
In visual communication, people glean insights about patterns of data by observing visual representations of datasets. Colormap data visualizations ("colormaps") show patterns in datasets by mapping variations in color to variations in magnitude. When people interpret colormaps, they have expectations about how colors map to magnitude,…
Descriptors: Concept Mapping, Visualization, Data Interpretation, Expectation
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Ting Sun; Stella Yun Kim – Educational and Psychological Measurement, 2024
Equating is a statistical procedure used to adjust for the difference in form difficulty such that scores on those forms can be used and interpreted comparably. In practice, however, equating methods are often implemented without considering the extent to which two forms differ in difficulty. The study aims to examine the effect of the magnitude…
Descriptors: Difficulty Level, Data Interpretation, Equated Scores, High School Students
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Sarah Klevan; Melanie Leung-Gagné; Tomoko M. Nakajima – Learning Policy Institute, 2024
Across the United States, there is an increased interest in improving school climate, reflecting a deepening understanding of the foundational role that school climate can play in supporting students' well-being, learning, and development. School climate is constructed from norms, expectations, and interpersonal relationships that come together to…
Descriptors: Educational Environment, Middle Schools, School Districts, Data Use
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Stoyanov, Slavi; Kirschner, Paul A. – Journal of Computer Assisted Learning, 2023
Background: Learning analytics (LA) collects, analyses, and reports data from the learning environment, to provide evidence of the effects of a particular learning design. Learning design (LD) outlines the conceptual framework for a meaningful interpretation of Learning analytics data. Objectives: The study aims to identify the most relevant…
Descriptors: Learning Analytics, Instructional Design, Data Interpretation, Literature Reviews
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Nina Zipser; Lisa Mincieli – Studies in Higher Education, 2025
This paper presents a framework for utilizing Student Evaluations of Teaching (SET) in faculty evaluations. Recognizing the ongoing debate about the validity of SET as a measure of teaching effectiveness, the authors agree with scholars who propose viewing SET as a tool for gauging 'student perceptions of learning'. They present a method that…
Descriptors: College Faculty, Faculty Evaluation, Student Evaluation of Teacher Performance, Evaluation Criteria
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William Norris; Roger Hanagriff; Don Edgar; Kirk Swortzel – Journal of Agricultural Education, 2025
Supervised Agricultural Experience (SAE) has been a critical component of School-Based Agricultural Education (SBAE) for decades. Formally called the 'home project', Rufus Stimson developed the concept of SAE in the early 20th century. This work-based learning concept provides students with experiential instruction that strengthens their…
Descriptors: Agricultural Education, Agriculture Teachers, Field Experience Programs, Experiential Learning
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Abdelmadjid Benmachiche; Abdelhadi Sahia; Soundes Oumaima Boufaida; Khadija Rais; Makhlouf Derdour; Faiz Maazouzi – Education and Information Technologies, 2025
In the context of massive open online courses (MOOCs), searching and retrieving information can be challenging because there is a huge amount of unstructured content, which creates a problem and makes it difficult for users to quickly find relevant lessons or resources. As a result, learners and teachers face significant barriers to accessing the…
Descriptors: MOOCs, Natural Language Processing, Artificial Intelligence, Search Engines
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Hanne Poelmans; Luciana Sacchetti; Sadia Vancauwenbergh; Stefano Piazza – Quality in Higher Education, 2024
World university rankings have had an impact on academic competition worldwide. The comparability of ranking results depends on how data is collected within each university. When data concepts are interpreted differently, data variety is introduced and ranking results cannot be used in a meaningful manner. In this case study, the effect of…
Descriptors: Foreign Countries, Universities, Rating Scales, Institutional Evaluation
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Rosanna Cole – Sociological Methods & Research, 2024
The use of inter-rater reliability (IRR) methods may provide an opportunity to improve the transparency and consistency of qualitative case study data analysis in terms of the rigor of how codes and constructs have been developed from the raw data. Few articles on qualitative research methods in the literature conduct IRR assessments or neglect to…
Descriptors: Interrater Reliability, Error of Measurement, Evaluation Methods, Research Methodology
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