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…

Teachers often use open-ended questions to promote students' deeper understanding of the content. These questions are particularly useful in K-12 mathematics education, as they provide richer insights into students' problem-solving processes compared to closed-ended questions. However, they are also challenging to implement in educational…

The fit of an item response model is typically conceptualized as whether a given model could have generated the data. We advocate for an alternative view of fit, "predictive fit", based on the model's ability to predict new data. We derive two predictive fit metrics for item response models that assess how well an estimated item response…

Background: Data literacy (DL) is vital for teachers, as it enables them to build on data and improve teaching and learning. Therefore, developing DL among pre-service teachers is critical. Objectives: The purpose of this study is threefold: to evaluate whether a feedback visualisation of peer assessment-based teaching approach (FVPA-based…

The present study operationalizes perceived positive regard in the form of a practical measure that can be applied in distance delivery settings. We collected data by surveying distance students at our university. The questions pertained to the quality of learning and the positive regard of the instructor as perceived by the students. Analytical…

Purpose: This paper aims to investigate the complex relationship between emotions, coping approaches and learning in error situations in the workplace. The study also examines the influence of individual error orientation, as well as psychological safety, and team learning behaviour as contextual factors. Design/methodology/approach: To measure…

The purpose of this study was to explore the factors that might affect learning performance and collaborative problem solving (CPS) awareness in science, technology, engineering, and mathematics (STEM) education. We collected and analyzed data on important factors in STEM education, including learning strategy and learning behaviors, and examined…

Learning analytics (LA) incorporates analyzing cognitive, social and emotional processes in learning scenarios to make informed decisions regarding instructional design and delivery. Research has highlighted important roles that emotions play in learning. We have extended this field of research by exploring the role of emotions in a relatively…

In this article, we propose using the Bayes factors (BF) to evaluate person fit in item response theory models under the framework of Bayesian evaluation of an informative diagnostic hypothesis. We first discuss the theoretical foundation for this application and how to analyze person fit using BF. To demonstrate the feasibility of this approach,…

This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT). MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to…

Data collected from online learning and tutoring systems for individual students showed strong autocorrelation or dependence because of content connection, knowledge-based dependency, or persistence of learning behavior. When the response data show little dependence or negative autocorrelations for individual students, it is suspected that…

Open-ended, short-answer questions, referred to as constructed responses (CR), allow students to express knowledge and skills through their own words. While CRs can reduce the likelihood of guessing correct answers, they also enable students to provide errant responses due to a lack of knowledge or a misunderstanding of the question.…

Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…

This study investigates the relationships among factor correlations, inter-item correlations, and the reliability estimates of subscores, providing a guideline with respect to psychometric properties of useful subscores. In addition, it compares subscore estimation methods with respect to reliability and distinctness. The subscore estimation…

The multidimensional item response theory (MIRT) models with covariates proposed by Haberman and implemented in the "mirt" program provide a flexible way to analyze data based on item response theory. In this report, we discuss applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the…