A learner can autonomously acquire knowledge by experiencing the world, without necessarily being explicitly taught. The contents and ways of this type of real-world learning are grounded on his/her surroundings and are self-determined by computing real-world information. However, conventional studies have not modeled, observed, or understood a…

As online learning has become an inevitable trend in the post-peak era of the COVID-19 pandemic, distributed pair programming (DPP) is gaining momentum in both education and industry. DDP serves as a collaborative programming approach and also benefits the development of computational thinking, a fundamental skill in today's world. This study…

Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…

In recent years, the emphasis on computational thinking (CT) has intensified as an effect of accelerated digitalisation. While most researchers are concentrating on defining CT and developing tools for its instruction and assessment, we focus on the characteristics of computational thinking problems (CTPs) -- activities requiring CT to be…

Background: Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K-12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to…

In recent years, when computational thinking (CT) has become increasingly important, utilizing machine learning (ML) techniques provides a revolutionary method for comprehending and improving cognitive skills for young students. However, few studies deepen the process of learning ML and CT. This exploratory study aims to investigate the impact of…

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…

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…

Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available; however, being…

Middle school students often enter Computer Science (CS) classes without previous CS or Computational Thinking (CT) instruction. This study evaluated how Code.org's block-based programming curriculum affects middle school students' CT skills and attitudes toward CT and CS. Sixteen students participated in the study. This was a mixed methods action…

In the dynamic educational context of Malaysia, this study examines the impact of integrating Unplugged Activities (UA) with Block-Based Programming (BBP) on improving the computational thinking (CT) skills of secondary students in full boarding schools in Northern Peninsular Malaysia. Using a quasi-experimental design and mixed-methods analysis,…

Pair programming (PP) can help improve students' computational thinking (CT), but the trajectory of CT skills and the differences between high-scoring and low-scoring students in PP are unknown and need further exploration. In this study, a total of 32 fifth graders worked on Scratch tasks in 16 pairs. The group discourse of three learning topics…

Fostering young learners' computational thinking in AI-based robots is a crucial issue in educational settings. However, there was the complexity of technology in supporting learning activities and the gender gap issue, so an appropriate strategy is needed to guide students to achieve the learning goals. In this study, an AI (Artificial…

Children with mathematical difficulties need to spend more time than typically achieving children on solving even simple equations. Since these tasks already require a larger share of their cognitive resources, additional demands imposed by the need to switch between tasks may lead to a greater decline of performance in children with mathematical…

The ability to properly evaluate one's own academic progress has long been considered a predictor of academic success. However, its distinctive role in the context of computational mathematics remains underexplored. Grounded in social cognitive theory, this study investigates the critical role of self-regulated learning (SRL) strategies in…