This paper proposes a new Information-Time index as the basis for item selection in computerized classification testing (CCT) and investigates how this new item selection algorithm can help improve test efficiency for item pools with mixed item types. It also investigates how practical constraints such as item exposure rate control, test difficulty (i.e., cut point), test length constraint, and test time constraint affect the effectiveness of this new item selection algorithm. Monte Carlo simulation techniques were used, and item parameters from the 1996 National Assessment of Educational Progress science assessment were used to build the data pool for an assessment combining 3 grades and consisting of 246 dichotomous items and 266 polytomous items. To create an Information-Time index, a response-time distribution was simulated. The Information-Time index was found feasible and effective in CCT with a mixed item pool. The Information-Time index for item selection worked well with other testing variables like item exposure control, test difficulty, and test constraints. (Contains 2 tables and 19 references.) (SLD)