Computational thinking skills are thought to have a significant part in almost every area and profession in the future. Yet, there is no sufficient number of studies in the literature to understand computational thinking and to reveal its nomological network. Therefore, the purpose of this study was to determine the relations between preservice…

Intelligent tutoring system (ITS) provides learners with step-by-step problem-solving support through scaffolding. Most ITSs have been developed in the USA and incorporate American instructional strategies. How do non-American students perceive and use ITS with different native problem-solving strategies? The present study compares Stoich Tutor,…

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…

Given the connection between problem-solving and computational thinking (CT), studying the connections between these two constructs is critical. This study focused on students' computational problem-solving strategies, specifically how they applied conditional logic to solve CT-related puzzles within a game-based learning environment called…

Teaching and learning Computational Thinking (CT) is at the forefront of educational interest. In the process of teaching and learning CT, learning strategies and tools play an important role. Efforts have been made to apply several learning strategies for teaching Computational Thinking. Among them, game-based learning and scaffolding are widely…

Computational thinking (CT) is an essential skill required for every individual in the digital era to become creative problem solvers. The purpose of this research is to investigate the relationships between computational thinking skills, the Big Five personality factors, and learning motivation using structural equation modeling (SEM). The…

Research trends on computational thinking (CT) and its learning strategies are showing an increase. The strategies are varying, for example is using games to provide enjoyment, engagement, and experience. To improve the high level of immersion and presence of game objects, learning strategies through games can be improved by virtual reality (VR)…

This study identified appropriate pedagogy for computational thinking in K-12 computer education. The Delphi technique was employed to collect different views, ideas and opinions derived a consensus from a panel of 12 international experts through a series of questionnaires. The experts have various experiences in computer science, computer…

Human-computer collaboration is an effective way to learn programming courses. However, most existing human-computer collaborative programming learning is supported by traditional computers with a relatively low level of personalized interaction, which greatly limits the efficiency of students' efficiency of programming learning and development of…

The key difference between math as math and math in science is that in science we blend our physical knowledge with our knowledge of math. This blending changes the way we put meaning to math and even the way we interpret mathematical equations. Learning to think about physics with math instead of just calculating involves a number of general…

Strategies are an important component of self-regulated learning frameworks. However, the characterization of strategies in these frameworks is often incomplete: (1) they lack an operational definition of strategies; (2) there is limited understanding of how students develop and apply strategies; and (3) there is a dearth of systematic and…

Computational thinking (CT) is considered a fundamental skill that everyone in the 21st century should have. Game-based learning (GBL) may be used to teach CT, and it's necessary to clarify how to design and implement game-based CT teaching. The literature was systematically searched for empirical studies published between 2011 and 2021.…

Being able to perform computational estimations efficiently is an important skill. Furthermore, computational estimation experiments are used to study general principles in strategy development. Rounding strategies are common in computational estimation. However, little is known about whether and when children use a mixed-rounding strategy (i.e.,…

Design-Based Learning and computational thinking (CT) are two key components that support each other specifically in the learning process involving the development of experimental design. Both components emphasize the importance of integration between computational thinking and design-based learning to support a creative, innovative and data…

Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students' learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study…