Presented at the Conference on Test Security 2022
This presentation will describe continued research and development into a simple and effective approach to identifying pairs of test takers with an unusually high number of matching scores (Smith, 2021; 2022). True score similarity index (SSI) analyses leverage item response theory (IRT) and the generalized binomial model (van der Linden & Sotaridona, 2006; Zopluoglu, 2017) which require specialized software, are based on relatively strong assumptions, and, depending on the length of the exam and number of examinees, require substantial computational resources. The approximation score similarity index (aSSI) method is not intended to outperform true SSI. Rather, it provides reasonable estimates of pairwise probabilities without specialized software, without requiring the same computational resources, and (in many cases) without item-level data. The purpose of the presentation will be to describe the aSSI method, further explore the conditions in which it works reasonably sufficiently by comparing it to true SSI, and to make practical recommendations for its use.
Speakers:
- Russ Smith, Alpine Testing Solutions
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