Effects of Calibration Sample Size and Item Bank Size on Ability Estimation in Computerized Adaptive Testing

Abstract

This study aimed to investigate the effects of calibration sample size and item bank size on examinee ability estimation in computerized adaptive testing (CAT). For this purpose, a 500-item bank pre-calibrated using the three-parameter logistic model with 10,000 examinees was simulated. Calibration samples of varying sizes (150, 250, 350, 500, 750, 1,000, 2,000, 3,000, and 5,000) were selected from the parent sample, and item banks that represented small (100) and medium size (200 and 300) banks were drawn from the 500-item bank. Items in these banks were recalibrated using the drawn samples, and their estimated parameters were used in post-hoc simulations to re-estimate ability parameters for the simulated 10,000 examinees. The findings showed that ability estimates in CAT are robust against fluctuations in item parameter estimation and that accurate ability parameter estimates can be obtained with a calibration sample of 150 examinees. Moreover, a 200-item bank pre-calibrated with as few as 150 examinees can be used for some purposes in CAT as long as it has sufficient information at targeted ability levels.