Quantum computing is the beginning of a new age for diverse industries, and educational technologies will significantly benefit from such quantum developments. This is a novel approach, applying quantum algorithms to enhance educational technologies, with no previous studies addressing the integration of quantum computing for personalized…

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…

Nowadays, physics learning in the classroom should no longer only focus on achieving academics. It must prepare students to face challenges in the future. One of the abilities that are important for learners is problem solving, and the problem-solving ability that is becoming increasingly important in today's digital era is computational thinking…

The integration of computational thinking (CT) into school curricula highlights its importance in preparing students for future success. Despite its recognised importance, there is a lack of understanding about effective CT teaching methods, particularly at primary and elementary levels. Previous studies highlight how teachers' beliefs in their…

Computational thinking is believed to be beneficial for Science, Technology, Engineering, and Mathematics (STEM) learning as it is closely related to many other skills required by STEM disciplines. There has been an increasing interest in integrating computational thinking into STEM and many studies have been conducted to examine the effects of…

Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…

Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…

Many educational and psychological studies have shown that the development of students is generally step-by-step (i.e. ordinal development) to a specific level. This study proposed a novel longitudinal learning diagnosis model with polytomous attributes to track students' ordinal development in learning. Using the concept of polytomous attributes…

Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…

The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In…

Teaching programming and computational thinking to young students has gained increasing attention in recent years. This great attention is attributed partially to the emergence of easy-to-use visual programming environments. These environments help students focus on the logic and concepts of programming and at the same time enhance their…

The cultivation of computational thinking (CT) skills is a key issue in talent cultivation today. This study reported a meta-analysis of 22 empirical studies to determine the effectiveness of using educational games to improve students' CT skills and the influence of various factors in instructional design on acquiring CT skills. The results…

Research showed that the capacity of making simple estimations begins to develop already at the age of five, but little is known about the early development of this estimation capacity and the strategies that underly it. The current study longitudinally followed the estimation capacity and strategies of 332 children from first to second grade of…

Many generalization studies in education are typically based on a sample of 30-70 schools while the inference population is at least twenty times larger. This small sample to population size ratio limits the precision of design-based estimators of the population average treatment effect. Prior work has shown the potential of small area estimation…

Unplugged activities as a low-cost solution to foster computational thinking (CT) skills seem to be a trend in recent years. However, current evidence of the effectiveness of unplugged activities in promoting students' CT skills has been inconsistent. To understand the potential of unplugged activities on computational thinking skills, a…