In this article, the authors explore the concerns surrounding academic dishonesty related to generative artificial intelligence (GAI). The authors argue that while there are valid worries about students using GAI in ways the displace student work, these anxieties are not new and have been observed with previous disruptive technologies such as the…

This case study reports on the perceptions and dialogic behaviors of 15 preservice K-12 teachers engaging in simulation-based teaching practice with AI-powered student agents. Data included transcripts of text-based classroom dialogue, interviews, observations, and conversation logs. Using mixed-methods analyses and a framework of ambitious…

Generative artificial intelligence (GenAI) is reshaping the research paradigm of doctoral education, with growing evidence suggesting that the use of artificial intelligence (AI) tools could promote innovative behaviour among doctoral students. However, the use of AI tools in scientific research should be approached with special caution, as…

The aim of the present study is to examine the effect of COVID-19 victimization experience (CVE) on university students' academic behaviors, which has not received sufficient attention in current research. Based on the job demands-resources model, which claims that insufficient resources and high demands can result in burnout, the present study…

This paper connects the problem of artificial intelligence (AI)-facilitated academic misconduct with crime-prevention based recommendations about the prevention of academic misconduct in more traditional forms. Given that academic misconduct is not a new phenomenon, there are lessons to learn from established information relating to misconduct…

Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…

Recycling waste is essential to mitigate environmental damage caused by human activity. Environmentally responsible behaviors, shaped during early ages, are closely linked to environmental attitudes, as demonstrated by prior research. This study aims to predict middle school students' recycling behaviors using machine learning algorithms. A…

The increasing use of complex machine learning models in education has led to concerns about their interpretability, which in turn has spurred interest in developing explainability techniques that are both faithful to the model's inner workings and intelligible to human end-users. In this paper, we describe a novel approach to creating a…

Online education has been expected to be the future of learning; it will never replace the value of traditional classroom experiences fully. Technical problems have less impact on offline education, which gives students more freedom to plan their time and stick to it. In addition, teachers cannot observe their students' behavior and activities…

Although previous studies have highlighted the problematic artificial intelligence (AI) usage behaviors in educational contexts, such as overreliance on AI, no study has explored the antecedents and potential consequences that contribute to this problem. Therefore, this study investigates the causes and consequences of AI dependency using ChatGPT…

Students are increasingly utilizing AI educational tools in their daily learning, complementing human instructors. Yet, little is known about how and when learning assistant type (Human vs. AI) influences students' innovation behavior. To better understand these ambiguities, based on self-determination theory and organizational climate theory, the…

AI integration in professional coursework has gained attention in higher education, offering potential improvements in learning and performance. However; the usage rate, accuracy, and patterns of AI tools across disciplines remain unclear. The impact of AI on students' learning and long-term outcomes still needs further investigation. This study…

Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an…

The development of Generative Artificial Intelligence (GenAI) tools like ChatGPT have transformed the academic landscape, offering learning opportunities while raising significant challenges regarding academic integrity. This study explores student perceptions and behaviours concerning academic integrity and the use of GenAI in the context of an…

Contribution: We present a framework for teachers to investigate the relationships between attributes of students' solutions in the process of problem solving or computational thinking. We provide visualization and evaluation techniques to find hidden patterns in the students' solutions which allow teachers to predict the specific behavior of…