Quality Assurance in Education, Vol. 26 No. 2, pp. 243-262
Surveys that include skill measures may suffer from additional sources of error compared to those containing questionnaires alone. Examples are distractions such as noise or interruptions of testing sessions, as well as fatigue or lack of motivation to succeed. This paper aims to provide a review of statistical tools based on latent variable modeling approaches extended by explanatory variables that allow detection of survey errors in skill surveys.
Psychometrika 83, 847–857 (2018)
Utilizing algorithms to generate items in educational and psychological testing is an active area of research for obvious reasons: Test items are predominantly written by humans, in most cases by content experts who represent a limited and potentially costly resource. Using algorithms instead has the appeal to provide an unlimited resource for this crucial part of assessment development.