The purpose of this study is to introduce a functional approach for modeling unfolding response data. Functional data analysis (FDA) has been used for examining cumulative item response data, but a functional approach has not been systematically used with unfolding response processes. A brief overview of FDA is presented and illustrated within the…

It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…

We investigated the effect of careless or insufficient effort (C/IE) responses in a study using Amazon's Mechanical Turk. A factor mixture model was used to identify latent classes based on the pattern of responses with biases and examine the effect of C/IE responses on the fit of the theoretical model.

For large-scale assessments, data are often collected with missing responses. Despite the wide use of item response theory (IRT) in many testing programs, however, the existing literature offers little insight into the effectiveness of various approaches to handling missing responses in the context of scale linking. Scale linking is commonly used…

Medical simulations allow trainees to work within teams to develop their self-regulated learning (SRL) and socially-shared regulated learning (SSRL) skills (Bransen et al., 2022). Both skillsets help to better prepare medical trainees for the multifaceted challenges inherent in clinical practice. SRL skills are imperative in empowering learners to…

Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…

Interactive tasks designed to elicit real-life problem-solving behavior are rapidly becoming more widely used in educational assessment. Incorrect responses to such tasks can occur for a variety of different reasons such as low proficiency levels, low metacognitive strategies, or motivational issues. We demonstrate how behavioral patterns…

A question asking for respondents' sex is one of the standard sociodemographic characteristics collected in a survey. Until now, it typically consisted of a simple question (e.g., "Are you…?") with two answer categories ("male" and "female"). In 2019, Germany implemented the additional sex designation divers for…

The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…

Nonresponse is an increasing problem in sample surveys and student surveys are no exception. When nonrespondents differ from respondents in meaningful ways, respondents may not be representative of the population. Hence, analyses of survey data may be biased and not generalizable to the population. In this chapter we provide an overview of…

In this research project we investigate the role of responses to anomalous data during modelling processes. Modelling is seen as a comprehensive practice that encompasses various aspects of scientific thinking; hence, it is an important style of scientific thinking, especially if analysed from a process-based perspective. Therefore, it provides…

Although numerous survey-based studies have found that students who identify as lesbian, gay, bisexual, or questioning (LGBQ) have elevated risk for many negative academic, disciplinary, psychological, and health outcomes, the validity of the types of data on which these results rest have come under increased scrutiny. Over the past several years,…

This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…

Data analytics is increasingly important to the operations and strategic growth of higher education institutions. In September 2019, three higher education professional associations issued a rare joint statement calling for the accelerated investment and intensified efforts to develop and deploy data analytics in support of campus decision making.…

We present a qualitative data analysis framework that integrates perspectives from theme analysis, cultural models analysis, grounded theory, and content analysis. We demonstrate how these research traditions are united in their aim to, first, uncover meaningful themes and, subsequently, to understand those themes' relationships to each other. To…