Assessment of Computational Thinking Skills

Abstract

In this chapter, approaches used to assess computational thinking skills will be discussed. Good examples of these approaches also form an important aspect of the chapter. As a first approach, we will focus on scales based on the individual’s perception of his/her computational thinking skill. These scales are frequently rating scales such as Likert type. Another approach is maximum performance tests to measure computational thinking. Achievement tests can be used with items that examine the individual’s computational thinking skills. Various types of items are used in tests, such as multiple-choice items or open-ended items. It is considered that these approaches will not be sufficient to measure computational thinking, which is a high-level skill. As a result, and as a third approach, rubric scoring the product that emerges from a work such as a performance task or project in which the individual will reveal his/her computational skills. A variation on the performance-based approach is application-based assessment. The performance of the individual is evaluated on an application that enhances computational thinking skills, such as Scratch and Alice. Computational thinking skill will be assessed or reported by examining the source code of a project prepared in the application. Methods that blend four approaches in various ways are also observed as a fifth approach. In this chapter, these approaches will be introduced and examples in the literature will be presented. Common and eligible examples will also be discussed in the context of design-based learning. It can be concluded that computational thinking skills cannot be measured with a single assessment method. An assessment system that includes more than one method is recommended for deeper analyze of computational thinking skill. It is also evident that this system should include open-ended or performance-based approaches rather than multiple-choice items, as computational thinking is a high-level skill. Therefore, open-ended or performance-based approaches are emphasized in the chapter. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.