With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

We live in a digital age, not least accelerated by the COVID-19 pandemic. It is all the more important in our society that students learn and master the key competence of algorithmic thinking to understand the informatics concepts behind every digital phenomena and thus is able to actively shape the future. For this to be successful, concepts must…

Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…