Search

This paper addresses the incorporation of problem decomposition skills as an important component of computational thinking (CT) in K-12 computer science (CS) education. Despite the growing integration of CS in schools, there is a lack of consensus on the precise definition of CT in general and decomposition in particular. While decomposition is commonly referred to as the starting point of (computational) problem-solving, algorithmic solution formulation often receives more attention in the classroom, while decomposition remains rather unexplored. This study presents "CTSKills", a web-based skill assessment tool developed to measure students' problem decomposition skills. With the data collected from 75 students in grades 4-9, this research aims to contribute to a baseline of students' decomposition proficiency in compulsory education. Furthermore, a thorough understanding of a given problem is becoming increasingly important with the advancement of generative artificial intelligence (AI) tools that can effectively support the process of formulating algorithms. This study highlights the importance of problem decomposition as a key skill in K-12 CS education to foster more adept problem solvers.

Algorithmic thinking (AT) is a critical skill in today's digital society, and it is indispensable not only in computer science-related fields but also in everyday problem-solving. As a foundational component of digital education and literacy, fostering AT skills is increasingly relevant for all students and should become a standard part of compulsory education. However, successfully integrating AT into formal education requires effective teaching strategies and robust and scalable assessment procedures. In this paper, we present the design and development process of the virtual Cross Array Task (CAT), a digital adaptation of an unplugged assessment activity aimed at evaluating algorithmic skills in Swiss compulsory education. The development process followed iterative design cycles, incorporating expert evaluations to refine the tool's usability, accessibility and functionality. A participatory design study played a dual role in shaping the platform. First, it gathered valuable insights from end users, including students and teachers, to ensure the tool's relevance and practicality in classroom settings. Second, it facilitated the collection and preliminary analysis of data related to students' AT skills, providing an initial evaluation of the tool's assessment capabilities across various developmental stages. This was achieved through a pilot study involving a diverse group of students aged 4 to 12, spanning preschool to lower secondary school levels. The resulting instrument features multilingual support and includes both gesture-based and visual block-based programming interfaces, making it accessible to a broad range of learners. Findings from the pilot study demonstrate the platform's usability and accessibility, as well as its suitability for assessing AT skills, with preliminary results showing its ability to cater to diverse age groups and educational contexts.

In recent years, the emphasis on computational thinking (CT) has intensified as an effect of accelerated digitalisation. While most researchers are concentrating on defining CT and developing tools for its instruction and assessment, we focus on the characteristics of computational thinking problems (CTPs) - activities requiring CT to be solved - and how they influence the skills students can develop. In this paper, we present a comprehensive framework for systematically profiling CTPs by identifying specific components and characteristics, while establishing a link between these attributes and a structured catalogue of CT competencies. The purposes of this framework are (i) facilitating the analysis of existing CTPs to identify which abilities can be developed or measured based on their inherent characteristics, and (ii) guiding the design of new CTPs targeted at specific skills by outlining the necessary characteristics required for CT activation. To illustrate the framework functionalities, we begin by analysing prototypical activities in the literature, a process that leads to the definition of a taxonomy of CTPs across various domains, and we conclude with a case study on the design of a different version of one of these activities, the Cross Array Task (CAT), set in different cognitive environments. This approach allows an understanding of how CTPs in different contexts display unique and recurring characteristics that promote the development of distinct skills. In conclusion, this framework can inform the development of assessment tools, improve teacher training, and facilitate the analysis and comparison of existing CT activities, contributing to a deeper understanding of competency activation and guiding curriculum design in CT education.