We argue that understanding the cognitive foundations of computational thinking will assist educators to improve children's learning in computing. We explain the conceptual relationship between executive functions and aspects of computational thinking. We present initial empirical data from 23 eleven year old learners which investigates the…

An educational team founded by Seymour Papert at MIT has developed an evolving series of computing environments designed to facilitate computational thinking. Papert outlined the goal of developing educational environments to facilitate the use of computer as a computational object in a seminal publication, "Teaching Children Thinking"…

Students completing undergraduate majors in chemistry are not typically required to undergo formal training in computer programming or coding. As a result, many chemistry students are graduating without skills in understanding, writing, or manipulating computer code. This skills gap places students at a disadvantage, considering the widespread and…

Background: The idea of computational thinking is underpinned by the belief that anyone can learn and use the underlying concepts of computer science to solve everyday problems. However, most studies on the topic have investigated the development of computational thinking through programming activities, which are cognitively demanding. There is a…

The COVID-19 pandemic, like past historical events such as the Vietnam War or 9/11, will shape a generation. Mathematics educators can seize this unprecedented opportunity to teach the principles of mathematical modeling in epidemiology. Compartmental epidemiological models, such as the SIR (susceptible-infected-recovered), are widely used by…

Human-driven carbon emissions have resulted in increased levels of dissolved carbon dioxide in the Earth's oceans. This dissolved carbon dioxide reacts with water to form carbonic acid, which impacts ocean acidity as well as the solubility of carbonate-containing compounds, with far-reaching impacts on marine ecosystems and the human communities…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…

The authors present a Web application they designed in the R programming language as an experiential learning tool for teaching production theory. The app simulates production decisions where a manager is tasked to find the optimal mixture of inputs through experimentation. Users of the application are instructed to use calculations and intuitions…

Previous research has invested much effort in understanding how programming can contribute to the development of young learners' computational thinking (CT) in traditional K-12 classroom settings. Relatively few studies have examined programming for CT in informal online communities, especially for large scale quantitative research. With the…

Despite the importance of computer science education and computational thinking, there have been limited examples of computer science education at K-12 classrooms that authentically represents the work of computer scientists, especially programming. One reason is the lack of a measurable definition of computational thinking and a programming…

Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…

Although generalizability theory (GT) designs have traditionally been analyzed within an ANOVA framework, identical results can be obtained with structural equation models (SEMs) but extended to represent multiple sources of both systematic and measurement error variance, include estimation methods less likely to produce negative variance…

Introductory programming courses (CS1) are difficult for novices. Inspired by "Problem solving followed by instruction" and "Productive Failure" approaches, we define an original "necessity-driven" learning design. Students are put in an apparently well-known situation, but this time they miss an essential ingredient…

Teaching computer programming to children and adolescents has become popular in recent years. This popularity has resulted in increased research into techniques for teaching introductory programming using visual languages, especially block-based languages. This study aims to explore new possibilities for teaching programming by adopting a hybrid…