Urban school environments present complex challenges at the intersection of mobility, safety, and environmental sustainability. Parents contribute to such issues, by adopting private motorized transport modes, especially cars, to take their pupils to schools. Hence, methods to assess the impacts of these habits and propose alternative transport solutions should be implemented. Traditional traffic sensing techniques can contribute to solving mobility issues by providing data that informs smarter urban planning, traffic management, and pollution mitigation strategies. However, such systems often fail to collect the granular traffic data on specific streets, such as in the case of areas around educational facilities. Innovative techniques, such as crowdsourcing through citizen science, offer a promising approach to filling these critical data gaps. Given these considerations, this study explores the potential of citizen science methodologies to collect traffic data in urban school zones by analyzing pilot cases in three Italian cities. The work contributes to research on using crowdsourced data for traffic estimation and validation by presenting various case studies, drawn from pilot experiments in northern and southern Italy, highlight regional differences and challenges specific to schools. Data analysis from the pilots demonstrates the value of citizen-generated data for identifying safety concerns and guiding targeted interventions.