Stochastic programming for individualized test assembly with mixture response time models.
Early research on response time modeling assumed that a test taker would show consistent response time behavior, often referred to as working speed, over the course of a test. Such models may be unrealistic for various reasons — a warm-up effect may cause a test taker to respond more slowly than exp...
| Publicado en: | Computers in Human Behavior Vol. 76; pp. 693 - 703 |
|---|---|
| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Elsevier B.V.
Nov2017
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=125081262&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 125081262 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: Nov2017 vid: 76 pid: 2410 pub: Elsevier B.V. artinfo: ui: 125081262 10.1016/j.chb.2017.04.060 ppf: 693 ppct: 10 formats: tig: atl: Stochastic programming for individualized test assembly with mixture response time models. aug: au: Veldkamp, Bernard P. Avetisyan, Marianna Weissman, Alexander Fox, Jean-Paul affil: University of Twente, The Netherlands Law School Admission Council, Newtown, PA, United States su: Computer assisted instruction Educational tests & measurements Reaction time Time sug: subj: Computer assisted instruction Educational tests & measurements Reaction time Time keyword: Automated test assembly Computerized adaptive testing Individualized testing Item selection Mixture models Response times Automated test assembly Computerized adaptive testing Individualized testing Item selection Mixture models Response times ab: Early research on response time modeling assumed that a test taker would show consistent response time behavior, often referred to as working speed, over the course of a test. Such models may be unrealistic for various reasons — a warm-up effect may cause a test taker to respond more slowly than expected to the early items, fatigue may cause a test taker to respond more slowly than expected toward the end of a test, or as time runs out the test taker may quickly guess the answers to the last items on a test. To take these variations in working speed into account, mixture response time models have recently been investigated. Until now, mixture response time models have only been applied for post hoc analyses. This research expands the use of these models by exploring their application in the context of the assembly of individualized computer-based assessments (CBAs). Response time constraints are probabilistic in nature. Stochastic programming was compared to three existing strategies for dealing with probabilistic constraints. Stochastic programming proved to be a very suitable strategy for solving test assembly problems with mixture response time models. Using stochastic programming, computer-based tests could be assembled in such a way that response time information could be used to the fullest extent. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|