Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…

This article considers the challenges of using artificial intelligence (AI) and machine learning (ML) to assist high-stakes standardised assessment. It focuses on the detrimental effect that even state-of-the-art AI and ML systems could have on the validity of national exams of secondary education, and how lower validity would negatively affect…

Computational thinking (CT) is a fundamental ability for learners in today's society. Although CT assessments and interventions have been studied widely, little is known about CT predictions. This study predicted students' CT achievement in the ICILS 2018 using five machine learning models. These models were trained on the data from five European…

Learners' emotional states might change during the learning process, and unpredictable variations of a person's emotions raise the demand for regular assessment of feelings during learning. In this paper, an AI-based decision framework is proposed and implemented for e-learning systems that identify suitable micro-brake activities based on the…

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…

The prevalence of information and communication technologies (ICTs) has brought about profound changes in the field of reading, resulting in a large and rapidly growing number of young digital readers. The article intends to identify key contextual factors that synergistically differentiate high and low performers, high and average performers, and…