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Wang, Lu; Steedle, Jeffrey – ACT, Inc., 2020
In recent ACT mode comparability studies, students testing on laptop or desktop computers earned slightly higher scores on average than students who tested on paper, especially on the ACT® reading and English tests (Li et al., 2017). Equating procedures adjust for such "mode effects" to make ACT scores comparable regardless of testing…
Descriptors: Test Format, Reading Tests, Language Tests, English
Li, Dongmei; Yi, Qing; Harris, Deborah – ACT, Inc., 2017
In preparation for online administration of the ACT® test, ACT conducted studies to examine the comparability of scores between online and paper administrations, including a timing study in fall 2013, a mode comparability study in spring 2014, and a second mode comparability study in spring 2015. This report presents major findings from these…
Descriptors: College Entrance Examinations, Computer Assisted Testing, Comparative Analysis, Test Format
Powers, Sonya; Li, Dongmei; Suh, Hongwook; Harris, Deborah J. – ACT, Inc., 2016
ACT reporting categories and ACT Readiness Ranges are new features added to the ACT score reports starting in fall 2016. For each reporting category, the number correct score, the maximum points possible, the percent correct, and the ACT Readiness Range, along with an indicator of whether the reporting category score falls within the Readiness…
Descriptors: Scores, Classification, College Entrance Examinations, Error of Measurement
Chen, Hanwei; Cui, Zhongmin; Zhu, Rongchun; Gao, Xiaohong – ACT, Inc., 2010
The most critical feature of a common-item nonequivalent groups equating design is that the average score difference between the new and old groups can be accurately decomposed into a group ability difference and a form difficulty difference. Two widely used observed-score linear equating methods, the Tucker and the Levine observed-score methods,…
Descriptors: Equated Scores, Groups, Ability Grouping, Difficulty Level
Kang, Taehoon; Chen, Troy T. – ACT, Inc., 2007
Orlando and Thissen (2000, 2003) proposed an item-fit index, S-X[superscript 2], for dichotomous item response theory (IRT) models, which has performed better than traditional item-fit statistics such as Yen's (1981) Q[subscript 1] and McKinley and Mill's (1985) G[superscript 2]. This study extends the utility of S-X[superscript 2] to polytomous…
Descriptors: Item Response Theory, Models, Computer Software, Statistical Analysis