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…

The generation of meaning in discourse is regarded as the process of knowledge-building, which can be analyzed by semantic waves. Combining the deep learning systems and polynomial fitting method, we present a method to compute multimodal semantic waves. With this method, four representative examples are discussed for the knowledge-building of…

Due to its task-based, gamified, and interactive features, unplugged programming activity has been widely employed in education and teaching as an activity away from electronic screens and other digital devices. There is ongoing debate over how to help K-9 pupils develop their computational thinking through unplugged programming activities. Based…

Facilitating Computer Science Unplugged (CS-unplugged) activities with reflective thinking activities lead students to in-depth reviews of their decisions and think of ways to solve the CS-unplugged problems. This study aims to evaluate the instruction enriched with reflective thinking activities to develop computational thinking skills. The study…

This study aims to examine the effect of augmented reality-assisted programming education supported by participatory design on the basic and computational thinking skills of preschoolers. In the study, a pretest-posttest single-group semi-experimental design, which is one of the quantitative research methods, was used. The study group of the…

Limited research has been conducted on the influence of computational thinking (CT) dispositions on students' mathematics performance and engagement at the secondary or junior high school level. This study aims to bridge this research gap by developing CT-integrated mathematics lessons that incorporate CT-focused problem-solving and modeling in…

This qualitative case study investigated how computational models can help students engage in scientific practice and influence their emotional, epistemic, and conceptual aspects. Twenty-four sixth-graders were guided to conduct scientific practices as they predicted and modified the computational models on food web using StarLogo Nova. Three…

Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimensional item response theory (MIRT) provides a unified framework and convenient statistical tool for item analysis, calibration, and scoring. However, the computational…

Understanding the magnitudes represented by numerals is a core component of early mathematical development and is often assessed by accuracy in situating numerals and fractions on a number line. Performance on these measures is consistently related to performance in other mathematics domains, but the strength of these relations may be…

Background: A resurgence in teaching coding in primary school classrooms has led to a pedagogical swing towards using physical computing and coding to develop students' use of algorithms, computational thinking, and problem-solving skills. Two obstacles impede the optimal development of these objectives: the availability of a suitable pedagogy and…

Computational thinking (CT) has been supported as an important skill every young person should possess for the 21st century, with possible implications for problem-solving, self-expression, and creativity. Numerous initiatives, both within and outside classroom settings, have been developed in response to policy mandates aiming at broadening…

The study focuses on the identification of relationships and/or rules between computational thinking (CT) concepts among the undergraduate students of Applied Informatics due to their attitudes towards mathematics. We analyze three CT concepts -- decomposition, pattern recognition, and algorithmic thinking. We assume that students who have a…

Computational modelling is widely used in biological science. Therefore, biology students need to learn computational modelling. However, there is a lack of evidence about how to teach computational modelling in biology and what the effects are on student learning. The purpose of this intervention-control study was to investigate how knowledge in…

Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…

Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…