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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
David Voas; Laura Watt – Teaching Statistics: An International Journal for Teachers, 2025
Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…
Descriptors: Statistics, Statistics Education, Regression (Statistics), Misconceptions
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
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
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
Bennett L. Schwartz – Metacognition and Learning, 2024
Retrospective confidence refers to the phenomenological experience of the level of certainty that retrieved information is, in fact, correct. Retrospective confidence judgments are examined across a range of sub-disciplines in psychology from perception to memory research, and in education and legal applications. This paper focuses on…
Descriptors: Memory, Recall (Psychology), Cues, Learning Processes
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
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
Ioana-Elena Oana; Carsten Q. Schneider – Sociological Methods & Research, 2024
The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…
Descriptors: Robustness (Statistics), Qualitative Research, Comparative Analysis, Decision Making
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
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
Sanetti, Lisa M. H.; Cook, Bryan G.; Cook, Lysandra – Learning Disabilities Research & Practice, 2021
Treatment fidelity refers to the extent to which an intervention is implemented as planned. If researchers do not assess and report treatment fidelity, or if treatment fidelity is shown to be low, findings from intervention studies are difficult to interpret, because the intervention may not have been implemented as planned. In this article, our…
Descriptors: Fidelity, Intervention, Program Implementation, Data Interpretation
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
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
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