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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
Iannario, Maria; Tarantola, Claudia – Sociological Methods & Research, 2023
This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…
Descriptors: Data Analysis, Data Interpretation, Probability, Models
Duschl, Richard; Avraamidou, Lucy; Azevedo, Nathália Helena – Science & Education, 2021
Grounded within current reform recommendations and built upon Giere's views (1986, 1999) on model-based science, we propose an alternative approach to science education which we refer to as the "Evidence-Explanation (EE) Continuum." The approach addresses conceptual, epistemological, and social domains of knowledge, and places emphasis…
Descriptors: Science Education, Epistemology, Data, Observation
Ludlow, Larry H.; O'Keefe, Theresa; Braun, Henry; Anghel, Ella; Szendey, Olivia; Matz, Christina; Howell, Burton – Practical Assessment, Research & Evaluation, 2022
Development of purpose is an important goal of post-secondary education. This study advances the measurement of purpose by (a) enriching the construct through incorporating the facet of horizon; (b) providing a framework for Rasch/Guttman Scenario score interpretation; and (c) providing evidence of convergent, divergent, and known groups validity.
Descriptors: Higher Education, Role of Education, Measurement, Item Response Theory
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
Shiri Mund – ProQuest LLC, 2022
The last decades have seen an unprecedented growth in the availability and accessibility of data, highly influenced by the ubiquity of digital media and the internet. As society contends with data's increasing impact on the nature of knowledge, communication, and privacy, it faces a pressing need for citizens who are intelligent producers and…
Descriptors: Data Interpretation, Literacy, 21st Century Skills, Measurement
Hunter, Rebecca A. – Journal of Chemical Education, 2021
An important objective of any analytical chemistry course is for students to generate and interpret data from the analysis of complex, real-world samples in order to assess the effectiveness of the analysis method, including the calibration. In this laboratory exercise, students directly compare calibration methods (external standards and standard…
Descriptors: Chemistry, Science Instruction, Food, Energy
Elgrishi, Noémie; Rountree, Kelley J.; McCarthy, Brian D.; Rountree, Eric S.; Eisenhart, Thomas T.; Dempsey, Jillian L. – Journal of Chemical Education, 2018
Despite the growing popularity of cyclic voltammetry, many students do not receive formalized training in this technique as part of their coursework. Confronted with self-instruction, students can be left wondering where to start. Here, a short introduction to cyclic voltammetry is provided to help the reader with data acquisition and…
Descriptors: Chemistry, Measurement, Data Collection, Data Interpretation
Knekta, Eva; Runyon, Christopher; Eddy, Sarah – CBE - Life Sciences Education, 2019
Across all sciences, the quality of measurements is important. Survey measurements are only appropriate for use when researchers have validity evidence within their particular context. Yet, this step is frequently skipped or is not reported in educational research. This article briefly reviews the aspects of validity that researchers should…
Descriptors: Factor Analysis, Surveys, Data Collection, Research Methodology
Fayed, Karim; Franken, Birgit; Berkling, Kay – Research-publishing.net, 2020
The iRead EU Project has released literacy games for Spanish, German, Greek, and English for L1 and L2 acquisition. In order to understand the impact of these games on reading skills for L1 German pupils, the authors employed an eye-tracking recording of pupils' readings on a weekly basis as part of an after-school reading club. This work seeks to…
Descriptors: Eye Movements, Measurement, Data Interpretation, Reading Skills
Wang, Jue; Engelhard, George, Jr. – Measurement: Interdisciplinary Research and Perspectives, 2016
The authors of the focus article describe an important issue related to the use and interpretation of causal indicators within the context of structural equation modeling (SEM). In the focus article, the authors illustrate with simulated data the effects of omitting a causal indicator. Since SEMs are used extensively in the social and behavioral…
Descriptors: Structural Equation Models, Measurement, Causal Models, Construct Validity
Rhemtulla, Mijke; van Bork, Riet; Borsboom, Denny – Measurement: Interdisciplinary Research and Perspectives, 2015
In this commentary, Mijke Rhemtulla, Riet van Bork, and Denny Borsboom write that they were delighted to see Bainter and Bollen's paper as a focus article in "Measurement." In their view, psychological researchers who use SEM rely too reflexively on reflective measurement, without sufficiently considering whether their indicators are…
Descriptors: Causal Models, Measurement, Data Interpretation, Statistical Data
Solomon, Bonnie J.; Sun, Sarah; Temkin, Deborah – Child Trends, 2021
With the passage of the 2015 Every Student Succeeds Act (ESSA), states were required to add a fifth indicator on "School Quality or Student Success" (SQSS) to their school accountability systems. An analysis of submitted ESSA state plans found that 13 states included measures of school climate as their SQSS indicator or incorporated…
Descriptors: School Districts, Learning Analytics, Educational Environment, Educational Quality
Borsboom, Denny; Wijsen, Lisa D. – Assessment in Education: Principles, Policy & Practice, 2016
The distinction between facts and moral values is highly desirable: science and politics should keep to their own territories. Traditionally speaking, science can be seen as an ivory tower, which attempts to do its job in isolation of external influences. Politics does not mandate methods of scientific research or standards of justification;…
Descriptors: Validity, Sciences, Politics, Definitions
Bainter, Sierra A.; Bollen, Kenneth A. – Measurement: Interdisciplinary Research and Perspectives, 2014
In measurement theory, causal indicators are controversial and little understood. Methodological disagreement concerning causal indicators has centered on the question of whether causal indicators are inherently sensitive to interpretational confounding, which occurs when the empirical meaning of a latent construct departs from the meaning…
Descriptors: Measurement, Statistical Analysis, Data Interpretation, Causal Models