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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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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
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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
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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
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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
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Leslie Rutkowski; David Rutkowski – Journal of Creative Behavior, 2025
The Programme for International Student Assessment (PISA) introduced creative thinking as an innovative domain in 2022. This paper examines the unique methodological issues in international assessments and the implications of measuring creative thinking within PISA's framework, including stratified sampling, rotated form designs, and a distinct…
Descriptors: Creativity, Creative Thinking, Measurement, Sampling
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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
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