The CTSkills App -- Measuring Problem Decomposition Skills of Students in Computational Thinking

TL;DR

This study presents "CTSKills", a web-based skill assessment tool developed to measure students' problem decomposition skills, and highlights the importance of problem decomposition as a key skill in K-12 CS education to foster more adept problem solvers.

Abstract

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.

Figures (15)

• Figure 1: Screenshots from Level 1, Level 2, and Level 3 of the CTSkills app.
• Figure 2: Screenshots from Question 1 (Q1) to Question 4 (Q4) of Level 1 of the CTSKills app.
• Figure 3: Pattern recognition, abstraction and generalisation to make code reusable.
• Figure 4: Percentage of Times Each Item Was Selected as Relevant for Question 1 - Level 1. This chart illustrates the percentage of times each item was selected as relevant, differentiating between correctly selected targets $S_X$ (in blue) and incorrectly selected non-targets $S_Y$ (in orange).
• Figure 5: Percentage of Times Each Item Was Selected as Relevant for Question Q1 across School Grades. This chart illustrates the percentage of times each item was selected as relevant, differentiating between correctly selected targets $S_X$ (in different shades of blue for each school grade) and incorrectly selected non-targets $S_Y$ (in different shades of orange for each school grade).