Open AccessGENERATIVE RESPONSE MODELING: LEVERAGING THE COMPUTER AS A TEST DELIVERY MEDIUM
Author(s) -
Bejar Isaac I.
Publication year - 1996
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.1996.tb01691.x
Subject(s) - computer science , computerized adaptive testing , item response theory , generative grammar , process (computing) , test (biology) , machine learning , artificial intelligence , psychometrics , statistics , mathematics , paleontology , biology , operating system
Generative response modeling is an approach to test development and response modeling that calls for the creation of items in such a way that the parameters of the items on some response model can be anticipated through knowledge of the psychological processes and knowledge required to respond to the item. That is, the computer would not merely retrieve an item from a database, as is the case in adaptive testing, but would compose it , or assist in doing so, according to desired specifications. This approach to assessment has implications for both the economics and validity of computer administered tests. To illustrate the concept, a system for measuring writing skills will be outlined where the examinee is expected to rewrite sentences, rather than just recognize errors in a sentence, using a multiple choice format. The possibility of estimating the psychometric parameters of items based on a psychological analysis of the response process will then be examined and shown to be feasible. Such estimates are less precise than estimates based on large samples of test takers. A Monte Carlo study is presented to investigate the possibility of compensating for that imprecision when estimating ability or proficiency. The paper concludes that a generative approach is feasible, and can be a mechanism for taking advantage of the considerable investment required for computer‐based testing.