Adaptive Assessment in an Instructor-Mediated System

Autor:	Robert E. Wray, Laura Hamel, Jeremiah T. Folsom-Kovarik
Rok vydání:	2013
Předmět:	Test item Estimation theory Calibration (statistics) End user Computer science Bayesian probability Direct control Data mining computer.software_genre computer Adaptive assessment
Zdroj:	Lecture Notes in Computer Science ISBN: 9783642391118 AIED
DOI:	10.1007/978-3-642-39112-5_61
Popis:	Instructor-mediated training systems give end users direct control over content, increasing acceptance but introducing new technical challenges. Decreased opportunity for parameter estimation limits the utility of item-response or Bayesian approaches to adaptive assessment. We present four adaptive assessment algorithms that require little data about test item characteristics. Two algorithms present about half as many items as random selection before producing accurate skill estimates. These algorithms enable adaptive assessment in training settings where calibration data is sparse.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::55f2f8dfa8e4e324d9c2420c79a2e347 https://doi.org/10.1007/978-3-642-39112-5_61 Zobrazit plný text záznamu