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…

This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…

A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization…

Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification.…

Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…

This dissertation aims to investigate the effect size measures of differential item functioning (DIF) detection in the context of cognitive diagnostic models (CDMs). A variety of DIF detection techniques have been developed in the context of CDMs. However, most of the DIF detection procedures focus on the null hypothesis significance test. Few…

Detection of students' ability levels is one of the common aims in educational studies. Cognitive Diagnosis Modeling approach has been used recently for the purpose of ability level detection by defined Q-matrices. To evaluate students' strengths and weaknesses, determine their mastery skills, and design instructions and interventions in learning…

This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…

Data mining has been successfully used by financial and retail companies since the mid-1960's to create predictive models and reveal unexpected relationships. However, it remains underutilized as a tool in educational research. Large-scale standardized assessment programs such as the Trends in International Mathematics and Science Study (TIMSS)…

Item response theory (IRT) has so many advantages than its precedent Classical Test Theory (CTT) such as non-changing item parameters, ability parameter estimations free from the items. However, in order to get these advantages, some assumptions should be met and they are; unidimensionality, normality and local independence. However, it is not…

An aggregation strategy is proposed to potentially address practical limitation related to computing resources for two-level multidimensional item response theory (MIRT) models with large data sets. The aggregate model is derived by integration of the normal ogive model, and an adaptation of the stochastic approximation expectation maximization…

Cross-national comparisons of responses to survey items are often affected by response style, particularly extreme response style (ERS). ERS varies across cultures, and has the potential to bias inferences in cross-national comparisons. For example, in both PISA and TIMSS assessments, it has been documented that when examined within countries,…

Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…

Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…

It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2] and the likelihood ratio statistic G[superscript…