Lye and Koh (2014) conceptualized Computational Thinking (CT) as the thinking skills that one can use to solve problems using computer technology. They distinguished between computational concepts - knowledge of CT, computational practices - the thinking skills that are important, and computational perspectives - the attitude component of CT. According to Lye and Koh (2014) computational practices are "problem-solving practices that occur in the process of programming" (p. 53), such as splitting the problem into sub-problems, using loops, iterations, tests and debugging to develop (partial) solutions, and reusing algorithms. They can be developed using programming tools. In this study we used the conceptualization of computational practices to study the thinking skills that young children use to solve a given problem - a simple programming task with a small robot. The study took place in grades two to six (age range 6-12) of a Dutch primary school. Forty-two pairs of children collaborated in the study. The children did not have any previous experience with programming. Pairs were from the same grade and consisted of boy duos (n=11), girl duos (n=16), and mixed duos (n=15). The pairs were asked to articulate their thinking process when solving the problem by thinking out loud. Each pair was video-taped. Based on the work of Hesse et al. (2015) about collaborative problem solving a rubric was developed to analyse the observations. Five sub-skills of CT skills were addressed in the rubric: problem decomposition, abstracting, data ordering, testing and debugging and solving problems. The analysis of the data showed that slightly less than half of the pairs successfully solved the task, in particularly pairs from the higher grades were successful. On average boy duos from the lower grades scored higher on the different sub-skills than girl or mixed duos from the same grade. In the higher grades no difference in average score was found between boy, girl and mixed pairs. Successful pairs structured their work, they collect all information before they start, eliminate options, take the time to go through the (possible) solution and work accurately. Implications for teaching and learning computational thinking skills will be discussed.

Lye, S. Y., & Koh, J. H.L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61. http://doi.org/10.1016/j.chb.2014.09.012 Hesse, F., Care, E., Buder, J. Sassenberg, K. & Griffin, P. (2015). A framework for teachable collaborative problemsolving skills. In P. Griffin & E. Care (Eds.). Assessment and teaching of 21st century skills (pp. 37-56). New York: Springer.