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Marasini, Donata; Quatto, Piero – Journal of Applied Quantitative Methods, 2011
Let X be a statistical variable representing student ratings of University teaching. It is natural to assume for X an ordinal scale consisting of k categories (in ascending order of satisfaction). At first glance, student ratings can be summarized by a location index (such as the mode or the median of X) associated with a convenient measure of…
Descriptors: Scientific Concepts, College Instruction, Student Evaluation of Teacher Performance, Data Interpretation
Peer reviewedRaymond, Mark R. – Evaluation and the Health Professions, 1989
Multidimensional scaling (MDS) and its potential use for research and evaluation in health-related professions are discussed. Useful data types, interpretation of results, and various applications of MDS are presented. MDS is less restrictive than factor analysis since it does not assume a linear relationship between the objects/variables of…
Descriptors: Allied Health Occupations, Cluster Analysis, Data Interpretation, Discriminant Analysis
Fisher, Mark A. – 1992
A model of graph comprehension is proposed including perceptual and memory processes. Multidimensional scaling (MDS), cluster analysis, and analysis of variance (ANOVA) were used to determine how college students with different mathematical experience read different types of bar graphs. Data were collected at the University of Oklahoma (Norman)…
Descriptors: Analysis of Variance, Classification, Cluster Analysis, College Students
Peer reviewedTrochim, William M. K., Ed. – Evaluation and Program Planning, 1989
Concept mapping is a structured conceptualization that can be used by groups to develop a conceptual framework that guides evaluation or planning. Twelve papers discuss concept mapping in evaluation/planning in terms of theory development; measurement, construct validity, and pattern matching; outcome assessment and internal validity;…
Descriptors: Concept Mapping, Construct Validity, Data Interpretation, Elementary Secondary Education


