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Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
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McClelland, Gary; Coombs, Clyde H. – Psychometrika, 1975
ORDMET is applicable to structures obtained from additive conjoint measurement designs, unfolding theory, general Fechnerian scaling, types of multidimensional scaling, and ordinal multiple regression. A description is obtained of the space containing all possible numerical representations which can satisfy the structure, size, and shape of which…
Descriptors: Algorithms, Computer Programs, Data Analysis, Matrices
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Powell, Jay C. – Guidance & Counselling, 1992
This commentary praises the clustering technique of data gathering from clients described by Carney (1992). It also cautions that analyzing qualitative data by quantitative means must be done with care, so that a matrix analysis and resulting interpretation of data gathered through the clustering technique, as Carney suggests, is valid and…
Descriptors: Counseling Techniques, Data Analysis, Matrices, Probability
National Council of Teachers of Mathematics, 2005
The sample assessment items in this volume are sorted according to the strands of number and operations, algebra, geometry, measurement, and data analysis and probability. Because one goal of assessment is to determine students' abilities to communicate mathematically, the writing team suggests ways to extend or modify multiple-choice and…
Descriptors: Probability, Matrices, Data Analysis, Geometry