The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…

Background: The recent discussion of introducing artificial intelligence (AI) knowledge to K-12 students, like many engineering and technology education topics, has attracted a wide range of stakeholders and resources for school curriculum development. While teachers often have to directly interact with external stakeholders out of the public…

Background and Context: Recognizing that digital technologies can enable economic transformation in Africa, computing education has been considered a subject relevant for all within the compulsory level of education. The implementation of the subject in many schools is, however, characterized by a myriad of challenges, including pedagogical…

Artificial intelligence (AI) has emerged as a prominent topic in K-12 education recently. However, pedagogical design has remained a major challenge, especially among young learners. Guided by the Zone of Proximal Development theory and AI education research literature, this design-based study proposes an analogy-based pedagogical approach to…

There is a growing consensus that AI literacy requires a holistic lens, including not only technical knowledge and skills but also social and ethical considerations. Yet, providing holistic AI education for upper-primary students remains challenging due to the abstract and complex nature of AI and a lack of pedagogical experiences in schools.…

The increasing prevalence of AI in everyday life has intensified the emphasis on teaching AI literacy to children. However, there is no consensus on the specific knowledge and skills that constitute children's AI literacy, resulting in varied AI learning materials for young people. We systematically searched for educational practices for…

Artificial intelligence (AI) education for K-12 students is an emerging necessity, owing to the rapid advancement and deployment of AI technologies. It is essential to take teachers' perspectives into account when creating ecologically valid AI education programmes for K-12 settings. However, very few studies investigated teacher perception of AI…

This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…

Over the last decade, there has been an explosion of national interest in computer science (CS) education. In response to this, several organizations and initiatives have emerged in recent years to expand the CS pipeline. However, within these broad and laudable efforts, one important area has been largely overlooked--the instruction of CS to…

Computational thinking (CT) is considered to be a critical problem-solving toolkit in the development of every student in the digital twenty-first century. Thus, it is believed that the integration of deeper learning in CT education is an approach to help students transfer their CT skills beyond the classroom. Few literature reviews have mapped…

The PrimaryAI project focuses on developing an upper elementary integrated curriculum that covers life science, artificial intelligence (AI), and computer science concepts. The PrimaryAI curriculum uses both problem-based learning (PBL) and game-based learning (GBL) to engage students and situates the curriculum in a real-world context. The…

This study aimed to integrate the results of prior studies on the effectiveness of AI education in K-12 Korean classrooms to draw systematic and comprehensive conclusions. To achieve this goal, a review of 64 studies on AI education in Korea that were conducted from 2019 to 2023 was subjected to a meta-analysis. The total effect size of AI…

This study presents an inclusive K-12 AI curriculum for elementary schools, focusing on six design principles to address gender disparities. The curriculum, designed by the researchers and an elementary teacher, uses tangible tools, and emphasizes collaboration in solving daily problems. The MANOVA results revealed initial gender differences in AI…

Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…

This article provides an in-depth look at how K-12 students should be introduced to Machine Learning and the knowledge and skills they will develop as a result. We begin with an overview of the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and briefly discuss each of the "Five Big Ideas in AI" that…