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Benton, Tom – Research Matters, 2020
This article reviews the evidence on the extent to which experts' perceptions of item difficulties, captured using comparative judgement, can predict empirical item difficulties. This evidence is drawn from existing published studies on this topic and also from statistical analysis of data held by Cambridge Assessment. Having reviewed the…
Descriptors: Test Items, Difficulty Level, Expertise, Comparative Analysis
Pfaffel, Andreas; Schober, Barbara; Spiel, Christiane – Practical Assessment, Research & Evaluation, 2016
A common methodological problem in the evaluation of the predictive validity of selection methods, e.g. in educational and employment selection, is that the correlation between predictor and criterion is biased. Thorndike's (1949) formulas are commonly used to correct for this biased correlation. An alternative approach is to view the selection…
Descriptors: Comparative Analysis, Correlation, Statistical Bias, Maximum Likelihood Statistics
Simpson, Adrian – Studies in Higher Education, 2017
Within higher education systems, different institutions deliver different patterns of disciplines. A simple analysis of the structure of that pattern of disciplines across institutions in one higher education system uncovers a surprising relationship. That is, the key dimensions which describe that structure align nearly perfectly with dimensions…
Descriptors: Higher Education, Classification, Intellectual Disciplines, Predictive Validity
Pfaffel, Andreas; Spiel, Christiane – Practical Assessment, Research & Evaluation, 2016
Approaches to correcting correlation coefficients for range restriction have been developed under the framework of large sample theory. The accuracy of missing data techniques for correcting correlation coefficients for range restriction has thus far only been investigated with relatively large samples. However, researchers and evaluators are…
Descriptors: Correlation, Sample Size, Error of Measurement, Accuracy
Liu, Ran; Koedinger, Kenneth R. – International Educational Data Mining Society, 2015
A growing body of research suggests that accounting for student specific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a…
Descriptors: Models, Regression (Statistics), Learning, Classification
Koon, Sharon; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2015
The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…
Descriptors: Classification, Regression (Statistics), Models, At Risk Students
Valdez, Alfred – International Journal of Higher Education, 2013
Metacognitive monitoring processes have been shown to be critical determinants of human learning. Metacognitive monitoring consist of various knowledge estimates that enable learners to engage in self-regulatory processes important for both the acquisition of knowledge and the monitoring of one's knowledge when engaged in assessment. This study…
Descriptors: Metacognition, Accuracy, Correlation, Validity
Chu, Chi Meng; Thomas, Stuart D. M.; Ogloff, James R. P.; Daffern, Michael – Assessment, 2013
Although violence risk assessment knowledge and practice has advanced over the past few decades, it remains practically difficult to decide which measures clinicians should use to assess and make decisions about the violence potential of individuals on an ongoing basis, particularly in the short to medium term. Within this context, this study…
Descriptors: Violence, Risk Assessment, Accuracy, Comparative Analysis