Extension usage examples:
Here's how our browser extension sees the article:
Components of the item selection algorithm in computerized adaptive testing - PubMed
Source: pubmed.ncbi.nlm.nih.gov
Article summary:
1. This article explains the three components of a conventional CAT item selection algorithm: test content balancing, the item selection criterion, and item exposure control.
2. Several noteworthy methodologies underlie each component, such as the maximized Fisher information criterion, the b-matching method, and the randomesque method.
3. Other important factors to consider when determining an appropriate CAT design are the computer resources requirement, the size of item pools, and the test length.
Article analysis:
The article is generally reliable in its presentation of information regarding components of a conventional CAT item selection algorithm. The author provides a comprehensive overview of several noteworthy methodologies that underlie each component, such as the maximized Fisher information criterion, the b-matching method, and the randomesque method. The article also mentions other important factors to consider when determining an appropriate CAT design such as computer resources requirement, size of item pools, and test length.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by providing an overview of different methods for each component without favoring any particular one over another. Furthermore, there is no promotional content or partiality present in this article; it is purely informational in nature. The author also does not make any unsupported claims or missing points of consideration; all claims are backed up with evidence from relevant sources. Additionally, possible risks associated with using these algorithms are noted throughout the article.
In conclusion, this article is reliable and trustworthy in its presentation of information regarding components of a conventional CAT item selection algorithm.