Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 4 |
Since 2006 (last 20 years) | 9 |
Descriptor
Data Interpretation | 10 |
Measurement | 10 |
Comparative Analysis | 2 |
Data | 2 |
Data Analysis | 2 |
Educational Research | 2 |
Elementary Secondary Education | 2 |
Evaluation Methods | 2 |
Foreign Countries | 2 |
Misconceptions | 2 |
Observation | 2 |
More ▼ |
Source
Author
Borsboom, Denny | 1 |
Carla Santorno | 1 |
Caruthers, J. Kent | 1 |
Donduran, Murat | 1 |
Drummond, Gordon B. | 1 |
Eddy, Sarah | 1 |
Feldman, Roger | 1 |
Henry Braun | 1 |
Iannario, Maria | 1 |
Iris C. Rotberg | 1 |
James Harvey | 1 |
More ▼ |
Publication Type
Reports - Descriptive | 10 |
Journal Articles | 9 |
Opinion Papers | 1 |
Education Level
Elementary Secondary Education | 2 |
Higher Education | 2 |
Early Childhood Education | 1 |
Elementary Education | 1 |
Kindergarten | 1 |
Postsecondary Education | 1 |
Primary Education | 1 |
Secondary Education | 1 |
Audience
Researchers | 1 |
Location
District of Columbia | 1 |
United Kingdom | 1 |
Laws, Policies, & Programs
Every Student Succeeds Act… | 1 |
Assessments and Surveys
Program for International… | 1 |
Trends in International… | 1 |
What Works Clearinghouse Rating
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
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
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
Malone, Susan Kohl; Zemel, Babette S. – Journal of School Nursing, 2015
The landscape of childhood health and disease has changed over the past century, and school nurses are now in a unique position to address the conditions that lead to chronic disease, such as obesity. Measuring body mass index (BMI) during childhood and adolescence is the recommended method for screening and/or monitoring obesity in school…
Descriptors: Body Composition, Measurement, Children, Adolescents
Feldman, Roger – Social Indicators Research, 2013
The use of "radar charts" is an increasingly popular way to present spatial data in a visually interesting format. Some authors recommend using "filled radar charts" to compare the performance of observational units. Filled radar charts are not appropriate for such comparisons because the size of the area within the polygon is not invariant to the…
Descriptors: Charts, Social Indicators, Observation, Misconceptions
Oren Pizmony-Levy; James Harvey; William H. Schmidt; Richard Noonan; Laura Engel; Michael J. Feuer; Henry Braun; Carla Santorno; Iris C. Rotberg; Paul Ash; Madhabi Chatterji; Judith Torney-Purta – Quality Assurance in Education: An International Perspective, 2014
Purpose: This paper presents a moderated discussion on popular misconceptions, benefits and limitations of International Large-Scale Assessment (ILSA) programs, clarifying how ILSA results could be more appropriately interpreted and used in public policy contexts in the USA and elsewhere in the world. Design/methodology/approach: To bring key…
Descriptors: Misconceptions, International Assessment, Evaluation Methods, Measurement
Rende, Sevinc; Donduran, Murat – Social Indicators Research, 2013
The Human Development Index (HDI) has been instrumental in broadening the discussion of economic development beyond money-metric progress, in particular, by ranking a country against other countries in terms of the well being of their citizens. We propose self-organizing maps to explore similarities among countries using the components of the HDI…
Descriptors: Well Being, Maps, Economic Development, Global Approach
Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2011
Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the…
Descriptors: Educational Research, Statistical Inference, Data Interpretation, Probability

Layzell, Daniel T.; Caruthers, J. Kent – Planning for Higher Education, 2002
Provides a basic overview of the concept of cost in higher education and related issues, discusses major consumers of higher education cost data and their perspectives, outlines the major sources of data on higher education costs, and describes some of the major (and perennial) issues related to higher education costs. (EV)
Descriptors: Costs, Data, Data Interpretation, Higher Education