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A growing body of research is focusing on integrating artificial intelligence (AI) and computational thinking (CT) to enhance student learning outcomes. Many researchers have designed instructional activities to achieve various learning goals within this field. Despite the prevalence of studies focusing on instructional design and student learning outcomes, how instructional efforts result in the integration of AI and CT in students' learning processes remains unclear. To address this research gap, we conducted a systematic literature review of empirical studies that have integrated AI and CT for student development. We collected 18 papers from four prominent research databases in the fields of education and AI technology: Web of Science, Scopus, IEEE, and ACM. We coded the collected studies, highlighting the students' learning processes in terms of research methodology and context, learning tools and instructional design, student learning outcomes, and the interaction between AI and CT. The integration of AI and CT occurs in two ways: the integration of disciplinary knowledge and leveraging AI tools to learn CT. Specifically, we discovered that AI- and CT-related tools, projects, and problems facilitated student-centered instructional designs, resulting in productive AI and CT learning outcomes. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) has received much attention in mathematics education in recent years, and researchers have begun to experiment with the integration of CT into mathematics education to promote students' CT and mathematical thinking (MT) development. However, there is a lack of empirical evidence and new theoretical perspectives on the mechanisms of interaction between CT and MT. To address this research gap, this study analyses the participants' thinking processes in solving programming-based mathematical problems from a flexibility perspective, focusing on the interplay between computational and mathematical thinking, that is, how CT and MT work together to influence and determine the problem-solver's choice of solution strategy. Using data collected from a large design-based study, we summarise two types of flexibility and six subtypes of flexibility demonstrated by participants in the programming-based mathematical problem-solving process using thematic analysis. These different types of flexibility provide researchers and mathematics educators with new theoretical perspectives to examine the interplay of CT and MT. Findings will also contribute toward student learning characteristics in programming-based mathematical problem-solving to sketch the big picture of how CT and MT emerge in complementary or mismatching ways. [ABSTRACT FROM AUTHOR]

Creativity, one of the cornerstones of students' 21st-century skills, is regarded as an important learning outcome of science, technology, engineering, arts, and mathematics (STEAM) education. Meanwhile, problem-based digital making (DM), which combines the child-friendly programming activities of DM with problem-solving elements, is an emerging instructional design to facilitate STEAM learning. This qualitative case study examines the implementation of a problem-based DM instructional program that used the block-based programming tool Scratch to cultivate the participants' creativity. Fifty-four middle school students (aged 10–14 years) in Hong Kong participated in the program, which totaled 10 contact hours over five consecutive weeks. Through triangulating students' DM artifacts, video recordings, field notes, and interviews, the researchers characterized the students' creative expression, examined the role of problem-based DM in encouraging creative work, and investigated the use of Scratch for mediating student creativity. The results showed that problem-based DM activities fostered students' creative expressions in the dimensions of novelty, utility, aesthetics, and authenticity. While Scratch mediated the way the students presented their solutions, it had limitations that hindered the students' digital artifact construction. The findings provide theoretical insights for framing creativity and offer practical implications for the implementation of problem-based DM in K–12 contexts. [ABSTRACT FROM AUTHOR]

This article explores the complex relational landscape of international partnerships where local and transnational education objectives are entangled. We present a methodological practice for experimenting with diagrams and maps. Our emphasis on spatial rendering of local/global relationality is intended to invite discussion about the postcolonial context of international education work and the geopolitics of transnational curriculum. We pursue a diagrammatic and archipelagic form of creative abstraction, which we present as a posthuman cartographic practice. To illustrate this practice, we focus on a specific international curriculum development project funded by the World Universities Network. [ABSTRACT FROM AUTHOR]

In this paper, we explore the challenges experienced by a group of Primary 5 to 6 (age 12–14) students as they engaged in a series of problem-solving tasks through block-based programming. The challenges were analysed according to a taxonomy focusing on the presence of computational thinking (CT) elements in mathematics contexts: preparing problems, programming, create computational abstractions, as well as troubleshooting and debugging. Our results suggested that the challenges experienced by students were compounded by both having to learn the CT-based environment as well as to apply mathematical concepts and problem solving in that environment. Possible explanations for the observed challenges stemming from differences between CT and mathematical thinking are discussed in detail, along with suggestions towards improving the effectiveness of integrating CT into mathematics learning. This study provides evidence-based directions towards enriching mathematics education with computation. [ABSTRACT FROM AUTHOR]