Controlling the Minimum Item Exposure Rate in Computerized Adaptive Testing: A Two-Stage Sympson–Hetter Procedure

Abstract

Computerized adaptive testing (CAT) can improve test efficiency, but it also causes the problem of unbalanced item usage within a pool. The effect of uneven item exposure rates can not only induce a test security problem due to overexposed items but also raise economic concerns about item pool development due to underexposed items. Therefore, this study proposes a two-stage Sympson–Hetter (TSH) method to enhance balanced item pool utilization by simultaneously controlling the minimum and maximum item exposure rates. The TSH method divides CAT into two stages. While the item exposure rates are controlled above a prespecified level (e.g., r_min) in the first stage to increase the exposure rates of the underexposed items, they are controlled below another prespecified level (e.g., r_max) in the second stage to prevent items from overexposure. To reduce the effect on trait estimation, TSH only administers a minimum sufficient number of underexposed items that are generally less discriminating in the first stage of CAT. The simulation study results indicate that the TSH method can effectively improve item pool usage without clearly compromising trait estimation precision in most conditions while maintaining the required level of test security.