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Assembly of parallel forms is an important step in the test development process. Therefore, choosing a suitable theoretical framework to generate well-defined test specifications is critical. The performance of different statistical targets of test specifications using the test characteristic curve (TCC) and the test information function (TIF) was investigated. Test length, the number of test forms, and content specifications are considered as well. The TCC target results in forms that are parallel in difficulty, but not necessarily in terms of precision. Vice versa, test forms created using a TIF target are parallel in terms of precision, but not necessarily in terms of difficulty. As sometimes the focus is either on TIF or TCC, differences in either difficulty or precision can arise. Differences in difficulty can be mitigated by equating, but differences in precision cannot. In a series of simulations using a real item bank, the two-parameter logistic model, and mixed integer linear programming for automated test assembly, these differences were found to be quite substantial. When both TIF and TCC are combined into one target with manipulation to relative importance, these differences can be made to disappear.

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This study compared gender groups on the processes used in writing essays in an online assessment. Middle‐school students from four grades responded to essays in two persuasive subgenres, argumentation and policy recommendation. Writing processes were inferred from four indicators extracted from students’ keystroke logs. In comparison to males, on average females not only obtained higher essay scores but differed from males in their writing processes. Females entered text more fluently, engaged in more macro and local editing, and showed less need to pause at locations associated with planning (e.g., between bursts of text, at sentence boundaries). That these differences were detected after controlling for essay scores suggests that they cannot be attributed solely to disparities in group writing skill.

In the present study, a procedure that has been used to select dichotomous items in computerized adaptive testing was applied to polytomous items. This procedure was designed to select the item with maximum weighted information. In a simulation study, the item information function was integrated over a fixed interval of ability values and the item with the maximum area was selected. This maximum interval information item selection procedure was compared to a maximum point information item selection procedure. Substantial differences between the two item selection procedures were not found when computerized adaptive tests were evaluated on bias and the root mean square of the ability estimate.