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Evaluating the Psychometric Characteristics of Generated Multiple-Choice Test Items.

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Title: Evaluating the Psychometric Characteristics of Generated Multiple-Choice Test Items.
Authors: Gierl, Mark J. (AUTHOR), Lai, Hollis (AUTHOR), Pugh, Debra (AUTHOR), Touchie, Claire (AUTHOR), Boulais, André-Philippe (AUTHOR), De Champlain, André (AUTHOR)
Source: Applied Measurement in Education. 2016, Vol. 29 Issue 3, p196-210. 15p.
Subjects: Psychometrics, Scale items, Psychological techniques, Item response theory, Examinations
Abstract: Item development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational testing situations. As a result, the psychometric characteristics of generated multiple-choice test items are largely unknown and undocumented. We present item analysis results from one of the first empirical studies designed to evaluate the psychometric properties of generated multiplechoice items using the results from a high stakes national medical licensure examination. The item analysis results for the correct option revealed that the generated items measured examinees' performance across a broad range of ability levels while, at the same time, providing a consistently strong level of discrimination for each item. Results for the incorrect options revealed that the generated items consistently differentiated the low from the high performing examinees. [ABSTRACT FROM AUTHOR]
Copyright of Applied Measurement in Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Item development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational testing situations. As a result, the psychometric characteristics of generated multiple-choice test items are largely unknown and undocumented. We present item analysis results from one of the first empirical studies designed to evaluate the psychometric properties of generated multiplechoice items using the results from a high stakes national medical licensure examination. The item analysis results for the correct option revealed that the generated items measured examinees' performance across a broad range of ability levels while, at the same time, providing a consistently strong level of discrimination for each item. Results for the incorrect options revealed that the generated items consistently differentiated the low from the high performing examinees. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Applied Measurement in Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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