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…

In recent years, modern board games (MBG) have attracted the attention of academics due to their innovative mechanics and mechanisms, which seem to facilitate the creation of spaces for the development of various aspects of computational thinking (CT). This article examines a number of MBG to identify those that contain CT-promoting mechanics. We…

Model-eliciting activities (MEAs) challenge students to interpret a problem and collaboratively create solutions using the engineering design process. This Innovation to Practice article describes how science, technology, engineering, and mathematics (STEM) teacher educators can use MEAs to build elementary teachers' understanding of computational…

Despite the increased number of quantitative effect sizes developed for single-case experimental designs (SCEDs), visual analysis remains the gold standard for evaluating methodological rigor of SCEDs and determining whether a functional relation between the treatment and the outcome exists. The physical length and range of values plotted on x and…

Despite the increased number of quantitative effect sizes developed for single-case experimental designs (SCEDs), visual analysis remains the gold standard for evaluating methodological rigor of SCEDs and determining whether a functional relation between the treatment and the outcome exists. The physical length and range of values plotted on x and…

Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

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…

Although computational thinking (CT) has emerged as an essential competence across all educational levels, limited research has focused on teachers' readiness for CT education, particularly within the context of early childhood education (ECE). This study involved 1,387 Chinese ECE teachers to identify their CT readiness profiles based on…

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…

This study aimed to examine teachers' classroom practices in the context of computational thinking skills and to determine their views on computational thinking. In the research process, the Q method was used in which quantitative and qualitative methods were used together. The participants of the research consist of 48 primary school teachers.…

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…

Block-based visual programming tools are widely used in elementary education. Nonetheless, these tools alone may not ensure the spontaneous and efficient acquisition of concepts and skills in computational thinking (CT). Using mind mapping as a form of scaffolding to facilitate the visualization of abstract thinking processes may enhance the…

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…