Statistical classification of item-response patterns into misconception groups in rule space

In an effort to further explore a specific aspect of rule-space theory, identification of students with respect to their error rules, three major questions were raised: (a) How do the discriminant-function approach (DA) and the k-nearest-neighbor approach (KNN) perform for the classification of each bivariate-normally- and non-bivariate-normally-distributed item-response patterns in rule space? (b) Is the use of rule-space model better than not using it for classifications? (c) What is the minimum pairwise distance for a 90% correct classification?

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Education, Tests and Measurements

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Kim, Sung-Hoon

Contributors dc:contributor

• Wardrop, James L.

• Education, Tests and Measurements

Statement dc:rights

• Copyright 1990 Kim, Sung-Hoon

Language dc:language

eng

Identifier

AAI9114297
(UMI)AAI9114297

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/19140