Using Item Response Theory and Adaptive Testing in Online Career Assessment
| Autor: | Brandon M. Turner, Nancy E. Betz |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Organizational Behavior and Human Resource Management
business.industry Cognitive Information Processing media_common.quotation_subject Machine learning computer.software_genre Scale (social sciences) Item response theory Trait The Internet Quality (business) Artificial intelligence Computerized adaptive testing business Psychology Social psychology Career assessment computer General Psychology Applied Psychology media_common |
| Zdroj: | Journal of Career Assessment. 19:274-286 |
| ISSN: | 1552-4590 1069-0727 |
| DOI: | 10.1177/1069072710395534 |
| Popis: | The present article describes the potential utility of item response theory (IRT) and adaptive testing for scale evaluation and for web-based career assessment. The article describes the principles of both IRT and adaptive testing and then illustrates these with reference to data analyses and simulation studies of the Career Confidence Inventory (CCI). The kinds of information provided by IRT are shown to give a more precise look at scale quality across the trait continuum and also to permit the use of adaptive testing, where the items administered are tailored to the individual being tested. Such tailoring can significantly reduce testing time while maintaining high quality of measurement. This efficiency is especially useful when multiscale inventories and/or a large number of scales are to be administered. Readers are encouraged to consider using these advances in career assessment. |
| Databáze: | OpenAIRE |
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