As computational thinking (CT) is new to teachers, they need support on how CT integration will work. This study examines the use of a hypothetical learning trajectory (HLT) to support teachers in integrating computational thinking into mathematics lessons utilizing GeoGebra. By employing the educational design research (EDR) methodology, the…

Solving systems of linear equations is a core concept in linear algebra and a wide variety of problems found in the sciences and engineering can be formulated as linear equations. This study sought to explore undergraduate students' development of the schema for solving systems of linear equations. The triad framework was used to describe the…

Computational Thinking (CT) skills are increasingly recognized as essential for junior high school students, especially in addressing the demands of the digital era. This study explores how CT skills--decomposition, pattern recognition, abstraction, and algorithmic thinking--manifest in learning statistics based on students' cognitive abilities. A…

Much attention has been paid to computational thinking (CT) as a problem-solving approach across various curricula, particularly in mathematics. Most studies solely used a digital instrument or examined transfer of program solving ability, neglecting the mathematics knowledge domain or how the novel digital instrument functions alongside the…

Recent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open-ended environments. AI…

In this study, we aimed to investigate the impact of cooperative learning on the computational thinking skills and academic performances of middle school students in the computational problem-solving approach. We used the pretest-posttest control group design of the quasiexperimental method. In the research, computational problem-solving…

Background: Empirical studies have revealed students' development of computational thinking (CT) and mathematical thinking (MT) during programming-based mathematical problem-solving, highlighting specific CT concepts or practices that serve as learning goals or outcomes. However, implementing programming-based mathematics instruction requires…

Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its…

This essay extends beyond the characteristics and discourse of word problems to, more generally, school mathematical problem-solving and the implications entailed by a predominant paper-and-pencil mode of learning and instruction since the modern era of education. Contrasting what I call "one-handed" (with paper-and-pencil) with…

Adaptive number knowledge represents the understanding and use of numerical characteristics and relations. However, there is a lack of knowledge about the role of adaptive number knowledge in solving problems that require the recognition of patterns. Therefore, we studied 61 sixth grade students' adaptive number knowledge and its connections to…

Computational thinking is seen as a basic and essential skill in the 21st century, but its development issue in accounting education is still relatively limited. Therefore, anchored in Wing's (2006) computational thinking theory, this study makes a case for developing problem-solving skills, which involve abstraction, decomposition,…

This is a conceptual paper based on existing literature aiming to provide practical information on designing and implementing activities to promote children's computational thinking. Computational thinking is a relatively new term in early childhood education that refers to a specific problem-solving thinking process involving various logical and…

The pretrained large language models have been widely tested for their performance on some challenging tasks including arithmetic, commonsense, and symbolic reasoning. Recently how to combine LLMs with prompting techniques has attracted lots of researchers to propose their models to automatically solve math word problems. However, most research…

Individuals learn to develop problem solving strategies and make connections between their mathematical ideas while programming, so they have the opportunity to improve their thinking skills. Scratch provides an environment to experience problem scenarios and encourages them to act out imagination while having fun. The purpose of the study is to…

Computational Thinking (CT) is a problem-solving process applicable across all disciplines. It has been defined as a 21st-century skill (Wing, "Communications of the ACM," 49(3), 33-35, 2006). Unfortunately, little pedagogical research is available to guide teachers and designers when devising a CT course. This study addresses this issue…