Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…

Longitudinal data analysis assumes that scales meet the assumption of longitudinal measurement invariance (i.e., that scales function equivalently across measurement occasions). This simulation study examines the impact of violations to the assumption of longitudinal measurement invariance on growth models and whether modeling the invariance…

Autonomy describes cognition or behavior that is self-directed, according to personal interests, and free from external influence. This construct is of importance to students who are deaf because it has been shown to be positively related to their post-school transition outcomes, and this population faces unique challenges in this area. To conduct…

This study developed an abbreviated form of Barron's (1953) Ego Strength Scale for use in research among college student samples. A version of Barron's scale was administered to 100 undergraduate college students. Using item-total score correlations and internal consistency, the scale was reduced to 18 items (Es18). The Es18 possessed adequate…

The nonequivalent groups with anchor test (NEAT) design is frequently used in test score equating or linking. One important assumption of the NEAT design is that the anchor test is a miniversion of the 2 tests to be equated/linked. When the content of the 2 tests is different, it is not possible for the anchor test to be adequately representative…

Research has found that the "a"-stratified item selection strategy (STR) for computerized adaptive tests (CATs) may lead to insufficient use of high a items at later stages of the tests and thus to reduced measurement precision. A refined approach, unequal item selection across strata (USTR), effectively improves test precision over the…

Specific Learning Disorder with impairment in reading (SLD-R) is the most widely diagnosed neurodevelopmental disorder. Individuals with SLD-R face many academic, social, and work challenges. To alleviate these difficulties, accommodations are provided, the most common being extended time for tests. The literature on extended time efficacy for…

Purpose: This study introduces a framework to produce very short versions of the MacArthur-Bates Communicative Development Inventories (CDIs) by combining the Bayesian-inspired approach introduced by Mayor and Mani (2019) with an item response theory-based computerized adaptive testing that adapts to the ability of each child, in line with…

As a method to shorten the test time of the Force Concept Inventory (FCI), we suggest the use of computerized adaptive testing (CAT). CAT is the process of administering a test on a computer, with items (i.e., questions) selected based upon the responses of the examinee to prior items. In so doing, the test length can be significantly shortened.…

The article deals with the innovative, cutting age solution within the language testing realm, namely computer adaptive language testing (CALT) in accordance with the NATO Standardization Agreement 6001 (NATO STANAG 6001) requirements for further implementation in foreign language training of personnel of the Armed Forces of Ukraine (AF of…

In this study, we propose aggregating test scores with unidimensional within-test structure and multidimensional across-test structure based on a 2-level, 1-factor model. In particular, we compare 6 score aggregation methods: average of standardized test raw scores (M1), regression factor score estimate of the 1-factor model based on the…

This study investigates potential bias that may arise when surveys include question items for which multiple units are elicited. Examples of such items include questions about experiences with multiple health centers, comparison of different products, or the solicitation of egocentric network data. The larger the number of items asked about each…

Questionnaire refinement and a process for selecting items for elimination are important tools for survey developers. One of the major obstacles in questionnaire refinement and elimination in surveys lies in one's ability to adequately and appropriately reconstruct a survey. Often times, surveys can be long and strenuous on the respondent,…

A growing body of research indicates that noncognitive factors are important predictors of students' academic and life success (e.g., Garcia, The need to address noncognitive skills in the education policy agenda (Briefing Paper No. 386), http://files.eric.ed.gov/fulltext/ED558126.pdf, 2014). Despite this evidence base, there are few…

A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory…