Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as…

Progress in understanding students' development of psychological literacy is critical. However, generative AI represents an emerging threat to higher education which may dramatically impact on student learning and how this learning transfers to their practice. This research investigated whether ChatGPT responded in ways that demonstrated…

This study explores the perspectives of Indian library professionals on the use of artificial intelligence (AI) in libraries. It aims to understand their knowledge, awareness, and views on AI and its challenges and opportunities. The research adopts a quantitative approach, using a closed-ended survey to collect data from 386 library professionals…

This survey investigates artificial intelligence (AI) literacy among academic library employees, predominantly in the United States, with a total of 760 respondents. The findings reveal a modest self-rated understanding of AI concepts, limited hands-on experience with AI tools, and notable gaps in discussing ethical implications and collaborating…

Amid the rapid evolution of artificial intelligence (AI), the intricate model structures and opaque decision-making processes of AI-based systems have raised the trustworthy issues in education. We, therefore, first propose a novel three-layer knowledge tracing model designed to address trustworthiness for an intelligent tutoring system. Each…

Unlike other technologies that augment human physical skills and abilities, artificial intelligence (AI) technologies interact with human thinking skills nurtured through various educational processes. Hence, advances in these technologies challenge the education sector to reimagine the suitable intellectual formation of students in the AI age. It…

Purpose: Given the increasing attention on ChatGPT in academia due to its advanced features and capabilities, this study aims to examine the links among Artificial intelligence (AI), knowledge sharing, ethics, academia and libraries in educational institutions. Moreover, this study also aims to provide a literature base while discussing recent…

A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recruited through an app-based platform. Individuals classified skin lesions from the International…

The popularity of artificial intelligence (AI) has highlighted the necessity of K-12 AI education, particularly at the elementary level. However, the lack of a comprehensive and age-appropriate AI curriculum integrated into school subjects, along with the abstract and complex nature of AI concepts, exacerbates student inequalities. Researchers…

The greater the proliferation of AI in educational contexts, the more important it becomes to ensure that AI adheres to the equity and inclusion values of an educational system or institution. Given that modern AI is based on historic datasets, mitigating historic biases with respect to protected classes (ie, fairness) is an important component of…

In the realm of education, the integration of AI literacy into computer science teaching is becoming increasingly crucial (Walsh et al., 2023; Voulgari et al., 2022; Velander et al., 2023). Teachers play a pivotal role in bridging the gap between research and practical knowledge transfer of AIrelated skills, necessitating a solid foundation in…

Knowledge Tracing (KT) is a task to model students' knowledge based on their coursework interactions within an Intelligent Tutoring System (ITS). Recently, Deep Neural Networks (DNN) showed superb performance over classical methods on multiple dataset benchmarks. While most Deep Learning based Knowledge Tracing (DLKT) models are optimized for…

This study aimed to identify pre-service science teachers' awareness of employing artificial intelligence in science education. It sought also to determine the reasons that led to this level of pre-service science teachers' awareness of employing AI in science education. The mixed-method was used with an interpretive sequential design. The…

K-12 artificial intelligence (AI) education requires cultivating students' computational thinking in the school curriculum so as to transfer their computational thinking to diverse problems and authentic contexts. However, students may be limited by traditional computational thinking development activities because they may have a lower degree of…

Background: The number of artificial intelligence (AI) literacy studies in K-12 education has recently increased, with most research focusing on primary and secondary education contexts. Little research focuses on AI literacy programs in early childhood education. Objectives: The aim of this mixed-methods study is to examine the feasibility of an…