A systematic mapping review and narrative synthesis of unplugged activities for developing computational thinking from an inclusive perspective

The ability to think computationally has become an essential ability that facilitates algorithm design, logical analysis and problem-solving. Unplugged Activities (UA) are considered as a practical starting point preparing students for more complex programming skills as they focus on algorithms, which are the key of Computational Thinking (CT). The aim of this study was to systematically map and narratively synthesize empirical research on unplugged activities for the development of CT, examining methodological characteristics, activity types, factors associated with learners’ performance and inclusive educational contexts. A total of 50 studies were identified and analyzed using defined inclusion and exclusion criteria and the results are reported as synthesis. Results indicate that the included studies most frequently reported learning outcomes related to algorithmic thinking, problem-solving, collaboration, motivation, satisfaction and engagement across various educational domains, such as STEM and Computer Science (CS), although differences in study designs and outcome measures limit conclusions regarding comparative effectiveness. The included studies reported a range of positive educational outcomes across different educational contexts. However, evidence from inclusive and special-education settings remains limited, preventing firm conclusions regarding the effectiveness of UA for learners with diverse educational needs.