Individuals solve arithmetic problems in different ways and the strategies they choose are indicators of advanced competencies such as adaptivity and flexibility, and predict mathematical achievement. Understanding the factors that encourage or hinder the selection of different strategies is therefore important for helping individuals to succeed…

In order to teach Computational Thinking (CT) skills to young students, Block-Based Programming Environments (BBPEs) are integrated into secondary school computer science (CS) education curricula. As a CT skill, abstraction is one of the prominent skills, which is difficult to enhance and measure. Researchers developed some scales for measuring…

The aim of this study is to compare the effects of unplugged and plugged-in activities on academic achievement and computational thinking (CT) skills of sixth-grade students. Mixed-method research was carried out to explore whether there were differences between the groups, and to learn the students' opinions and experiences regarding the…

The purpose of the qualitative study was to investigate experiences of first-time board-game users (29 elementary school students) in playing "Coding Ocean" (CO) to learn computational thinking. CO was a two-team strategy board game and was designed for children developing basic understanding of computational thinking. Participation…

Public administration is struggling to contend with a substantial shift in practice fueled by the accelerating adoption of information technology. New skills, competencies and pedagogies are required by the field to help overcome the data-skills gap. As a means to address these deficiencies, we introduce the Data Science Literacy Framework, a…

With the increasing importance of Computational Thinking (CT) at all levels of education, it is essential to have valid and reliable assessments. Currently, there is a lack of such assessments in upper primary school. That is why we present the development and validation of the competent CT test (cCTt), an unplugged CT test targeting 7-9 year-old…

The aim of this study is to evaluate a professional development program applied to primary school teachers for unplugged algorithmic thinking activities and to improve it based on this evaluation. In this context, data were collected for the improvement of the program by consulting the opinions of the teachers. The professional development program…

In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…

Coding is a process often associated with computers. Nevertheless, coding is a thought process that can be mastered even without a computer. In NSW, primary students are introduced to computational and algorithmic thinking as early as Stage 1. Yet, teaching coding to young students is not always easy for teachers, mostly because the process is…

In this case study, we investigate one teacher's implementation of DNR-based combinatorics curriculum in their high school discrete mathematics class. By examining the teacher's practices in whole-class discussions of two counting problems, we study how they advanced a variety of ways of thinking to support the development of a set-oriented way of…

The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle international survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across…

Computing has become an essential part of today's primary and secondary school curricula. In recent years, K-12 computer education has shifted from computer science itself to the broader perspective of computational thinking (CT), which is less about technology than a way of thinking and solving problems--"a fundamental skill for everyone,…

When working with multimodal Bayesian posterior distributions, Markov chain Monte Carlo (MCMC) algorithms have difficulty moving between modes, and default variational or mode-based approximate inferences will understate posterior uncertainty. And, even if the most important modes can be found, it is difficult to evaluate their relative weights in…

The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the…

Structural equation modeling (SEM) is being applied to ever more complex data types and questions, often requiring extensions such as regularization or novel fitting functions. To extend SEM, researchers currently need to completely reformulate SEM and its optimization algorithm -- a challenging and time-consuming task. In this paper, we introduce…