Predicting academic performance in Educational Data Mining has been a significant research area. This involves utilizing machine learning techniques to analyze data from educational settings. Predicting student academic performance is a complex task due to the influence of multiple factors. This research uses supervised machine-learning approaches…

A series of experiments conducted in Central Europe (Hungary, Austria) and East Asia (Japan) probed whether 5- to 10-year-old children (n = 436, 213 female) and adults (n = 71, 43 female; all data collected between July 2020 and May 2023) would infer traits and choose partners accordingly, in a novel touchscreen game. The participants observed…

Generative artificial intelligence (AI) has the potential to revolutionize social science research. However, researchers face the difficult challenge of choosing a specific AI model, often without social science-specific guidance. To demonstrate the importance of this choice, we present an evaluation of the effect of alignment, or human-driven…

Augmented reality (AR) is one of the key emerging educational technologies that has gained traction in recent years. Subsequently, researchers have also begun to acknowledge AR's potential as a pedagogical tool that can be integrated into school curricula for environmental education. Such progress is important since the urgency of the climate…

In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…

Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…

Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…

As China joined the World Trade Organization (WTO) and its national strength continued to grow, enthusiasm for learning Chinese has been heating up globally. Chinese language education has gradually integrated into the education systems of more countries, becoming a significant focus of attention and study. However, despite the increasing demand…

Recently, there has been a plethora of studies about students' attitudes toward the use of artificial intelligence (AI) technologies in education, particularly in higher education and language education; however, research on AI use in high school settings has gained relatively little attention, leaving a huge research gap in the literature. This…

Throughout their years of education, health science graduate and professional students complete countless hours of studying and taking exams, which can elevate the stress on these students in addition to their natural strains outside of school. Identifying a method to help reduce academic stress could be critical to positively impact student…

The literature on generative "Artificial Intelligence" (AI) in education primarily focuses on its immediate benefits and applications, such as personalized learning, student engagement, and content generation. However, there is a notable absence of empirical research concerning the holistic use of generative AI within educational…

This study aimed to explore the impact of basic psychological needs on satisfaction with using generative AI and ChatGPT in particular. Further, an adaptation of the "Basic Psychological Need Satisfaction for Technology Use" (BPN-TU) scale was conducted throughout the study. The study developed a unique research model based on the…

Given the growing demands in computer science (CS) education and the rapid progress of artificial intelligence (AI) technologies, this article presents a comprehensive review of selected empirical studies on AI in CS education, published from 2003 to 2023. The data for this review were sourced from the Web of Science, ACM Digital Library, IEEE…

This article examines the ethical implications of utilizing generative AI (GenAI) tools in adult higher education. It clarifies how traditional AI applications, such as plagiarism detection and adaptive quizzes, differ from generative systems that create new content. Core tensions include protecting student data, mitigating algorithmic bias,…

The computer has evolved from a tool to a privileged position where architectural design takes shape. Given that students are expected to work primarily in a computational environment and frequently in a collaborative way, some questions challenge and inspire us to consider new ways and methods that will aid in the creation and sharing of…