Gli effetti cognitivi del pensiero computazionale

In Europe, a significant percentage of 13-year-old students lacks essential digital and problem-solving skills that are crucial for contemporary societies. Computational Thinking (CT), integrated into school curricula in various countries, emerges as a promising educational program to cultivate 21st-century skills, including digital literacy and analytical thinking. CT involves a problem-solving approach inspired by computer science, encouraging the breakdown of complex problems into manageable parts and fostering systematic thinking. This thesis focuses on coding, which is a component of CT that involves creating, modifying, and evaluating program text, symbols, and familiarity with programming concepts. Teaching tools for CT include unplugged coding, educational robotics (ER), and plugged/virtual coding. While the integration of CT into schools is widely acknowledged, research on the cognitive benefits of CT and coding interventions, especially through randomized trials, is still limited. Existing studies suggest positive effects on computational thinking, problem-solving, and executive functions abilities. However, non-experimental or quasi-experimental studies underpin most of the existing literature. More robust evidences is needed. The studies presented in the present thesis aim to address this gap by examining the consistency and generalizability of effects across different executive functions and age groups. Starting from the results of previous studies, the present thesis investigated the cognitive effects of CT interventions on children of different age (range from 4 to 16 years), with the aim of exploring the cognitive effects of computational thinking. We first conducted a systematic review and meta-analytic study on the cognitive effects of computational thinking, Study 1 was a review of the effectiveness of CT intervention on the development of core and higher order executive functions, trying to gain a comprehensive understanding of the cognitive effects of computational thinking, with a specific focus on the age range 4-16 years. Second, we explored how the gains of preschoolers in coding skills following an intervention based on a combination of unplugged coding and educational robotics transfer to plugged (computer-based) coding abilities and to EFs such as planning, response inhibition, and visuo-spatial skills. Study 2 investigated the effects of tangible coding intervention on preschoolers’ EFs and visuo-spatial skills through a cluster randomized controlled trial. Forty-seven (47) preschoolers from 4 class groups, with no prior exposure to coding, were randomly assigned to an experimental (unplugged coding and ER, 2 classes) or control (standard school activities, 2 classes) instructional condition. Third, we tested the age-related effects of coding interventions, Study 3 addressed this research question. Four-hundred thirty-seven (437) primary school children, attending the first year or the fourth year of primary school, from 5 schools from different socio-economic status (SES) participated in the study. None of the children had been previously exposed to coding. Within each age group (first or fourth grade) children were assigned to a treatment and a control group. The first-grade group comprised 273 children: 128 assigned to the treatment condition and participating in coding labs immediately after the pretest (T1) and 145 controls, assigned to standard STEM activities (math and technology) and receiving the coding intervention only after the posttest (T2). Although the teaching of CT is compulsory, we still know very little about the effectiveness of CT programs and the cognitive functions these programs work best on. Consequently, recommendations for instructional practice are also lacking. Testing the effectiveness of CT intervention may help develop such recommendations and identify the best instructional tools and programs for teaching coding from an early age . Overall, the results