Guessing and cognitive diagnostics: A general multicomponent latent trait model for diagnosis

Lutz, Megan Elyse

Title:

Guessing and cognitive diagnostics: A general multicomponent latent trait model for diagnosis

dc.contributor.advisor	Embretson, Susan E.
dc.contributor.author	Lutz, Megan Elyse
dc.contributor.committeeMember	Hertzog, Christopher
dc.contributor.committeeMember	Morley, Tom
dc.contributor.committeeMember	Spieler, Daniel
dc.contributor.committeeMember	Templin, Jonathan
dc.contributor.department	Psychology
dc.date.accessioned	2015-06-08T18:14:33Z
dc.date.available	2015-06-09T05:30:07Z
dc.date.created	2014-05
dc.date.issued	2014-04-02
dc.date.submitted	May 2014
dc.date.updated	2015-06-08T18:14:33Z
dc.description.abstract	A common issue noted by detractors of the traditional scoring of Multiple Choice (MC) tests is the confounding of guessing or other false positives with partial knowledge and full knowledge. The current study provides a review of classical test theory (CTT) approaches to handling guessing and partial knowledge. When those methods are rejected, the item response theory (IRT) and cognitive diagnostic modeling (CDM) approaches, and their relative strengths and weaknesses, are considered. Finally, a generalization of the Multicomponent Latent Trait Model for Diagnosis (MLTM-D; Embretson & Yang, 2013) is proposed. The results of a simulation study are presented, which indicate that, in the presence of guessing, the proposed model has more reliable and accurate item parameter estimates than the MLTM-D, generally yielding better recovery of person parameters. Discussion of the methods and findings, as well as some suggested directions for further study, is included.
dc.description.degree	Ph.D.
dc.embargo.terms	2015-05-01
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/53446
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Cognitive diagnostic models
dc.subject	Achievement testing
dc.title	Guessing and cognitive diagnostics: A general multicomponent latent trait model for diagnosis
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Embretson, Susan E.
local.contributor.corporatename	College of Sciences
local.contributor.corporatename	School of Psychology
relation.isAdvisorOfPublication	19f0fa71-2cea-4ce0-851b-e019cc56c45a
relation.isOrgUnitOfPublication	85042be6-2d68-4e07-b384-e1f908fae48a
relation.isOrgUnitOfPublication	768a3cd1-8d73-4d47-b418-0fc859ce897d
thesis.degree.level	Doctoral