An Unfolding Analysis Of Cognitive Preferences

This study represents a reanalysis of Heath's (1963) data using Coombs' unfolding technique. Some additional objectives of this study are to find the dimensions underlying the cognitive preferences, to test Heath's first two hypotheses in terms of individuals as well as clusters, and to compare cluster and individual analyses. The first dimension, which goes from Applications to Memory to Principles to Questioning , accounts for over half of the individuals and over two‐thirds of the clusters. A two‐dimensional configuration accounts for 90% of the individuals and 99% of the clusters. The ordering along the second dimension goes from Memory to Application to Questioning to Principles. The analyses of clusters and individuals were shown to give identical solutions. With respect to the first dimension alone as well as with consideration of both dimensions, the following hypotheses were supported: (a) that the Physical Science Study Curriculum group and the control group would be generally located in different regions of the same joint space, the PSSC group being more densely distributed than controls in regions near Principles and Questioning, the controls being more densely distributed than the PSSC group in regions near Memory and Applications; (b) that achievement scores for PSSC clusters would be higher in regions near Principles and Questioning than in regions near Applications and Memory; and (c) that the region‐achievement relationship hypothesized in “b” would be stronger in the PSSC group than in the control group. Implications following from the analysis were discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108304/1/ets200128.pd

Tailoring Explanations for the User

In order for an expert system to provide the most effective explanations, it should be able to tailor its responses to the concerns of the user. One way in which explanations may be tailored is by point of view A method is presented for representing the knowledge to support different points of view in the current domain. In addition, we present a method for determining the point of view to take by inferring the user's goal within a brief discourse segment. The advising system's response to the derived goal depends on the strength of its belief in the inference for which a method of determination is also provided. This information enables the system to decide what answer to give to a question, which kind of justification is relevant, and when to provide it. Some details of the current implementation are included

A Structural Theory For The Perception Of Morse Code Signals And Related Rhythmic Patterns.

PhDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/184637/2/6708370.pd

Multidimensional scaling

93 p.; 21 cm

Tailoring Explanations for the User 1

In order for an expert system to provide the most effective explanations, it should be able to tailor its responses to the concerns of the user One way in which explanations may be tailored is by point of view A method is presented for representing the knowledge to support different points oi view in the current domain In addition, we present a method for determining the point of view to take by inferring the user's goal within a brief discourse segment The advising system's response to the derived goal depends on the strength of its belief in the inference for which a method of determination is also provided This information enables the system to decide what answer to give to a question, which kind of justification is relevant, and when to provide it Some details of the current implementation are included