A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…

The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs)…

Despite the increasing demand for diagnostic information, observed subscores have been often reported to lack adequate psychometric qualities such as reliability, distinctiveness, and validity. Therefore, several statistical techniques based on CTT and IRT frameworks have been proposed to improve the quality of subscores. More recently, DCM has…

Adult learning involves the analysis and synthesis of knowledge to become competent, which cannot be assessed only by traditional assessment tool and didactic learning methods. Stimulation of higher domains of cognitive learning needs to be inculcated to reach a better understanding of the subject rather than traditional assessment tools that…

This research aimed to develop a valid and reliable test to be used to detect sixth grade students' misconceptions and errors regarding the subject of fractions. A misconception diagnostic test has been developed that includes the concept of fractions, different representations of fractions, ordering and comparing fractions, equivalence of…

When there are no personal consequences associated with test performance for examinees, rapid guessing (RG) is a concern and can differ between subgroups. To date, the impact of differential RG on item-level measurement invariance has received minimal attention. To that end, a simulation study was conducted to examine the robustness of the…

With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…

Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…

The present study examined the performance of the bi-factor multidimensional item response theory (MIRT) model and higher-order (HO) cognitive diagnostic models (CDM) in providing diagnostic information and general ability estimation simultaneously in a listening test. The data used were 1,611 examinees' item-level responses to an in-house EFL…

Purpose: This study aimed to compare the cut scores obtained by the Extended Angoff and Contrasting Groups methods for an achievement test consisting of constructed-response items. Research Methods: This study was based on survey research design. In the collection of data, the study group of the research consisted of eight mathematics teachers for…

The main objective of the article is to compare several methods of evaluating multiple-choice options through classical item analysis. The methods subjected to examination include the tabulation of choice distribution, the interpretation of trace lines, the point-biserial correlation, the categorical analysis of trace lines, and the investigation…

There is an increasing demand for assessments that can provide more fine-grained information about examinees. In response to the demand, diagnostic measurement provides students with feedback on their strengths and weaknesses on specific skills by classifying them into mastery or nonmastery attribute categories. These attributes often form a…

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class…

Language proficiency testing serves an important function of classifying examinees into different categories of ability. However, misclassification is to some extent inevitable and may have important consequences for stakeholders. Recent research suggests that classification efficacy may be enhanced substantially using computerized adaptive…

The Angoff standard setting method relies on content experts to review exam items and make judgments about the performance of the minimally proficient examinee. Unfortunately, at times content experts may have gaps in their understanding of specific exam content. These gaps are particularly likely to occur when the content domain is broad and/or…