Positioning citizen science within the broader historical public engagement framework demonstrates how it has the potential to effectively tackle research and innovation issues. Citizen science approaches have their own challenges, which need to be considered in order to achieve this aim and contribute to wider and deeper public engagement. However, programme evaluations, which discuss lessons learned in engaging the public and other stakeholders with science are rare. To address this gap, we present the H2020-funded DITOs project and discuss the use of logic models in citizen science. We share the project’s assumptions, design considerations for deeper engagement and its impact pathways demonstrating how logic models can be utilised in citizen science to monitor programme effectiveness and for their successful implementation. We hope that this work will inspire citizen science practitioners to use similar tools and by doing so, share their experiences and potential barriers. This knowledge is essential for improving the way citizen science is currently practiced and its impacts to both science and society.

中文翻译：

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为公众参与科学做出积极贡献的公民科学影响途径

将公民科学置于更广泛的历史公众参与框架内，展示了它如何具有有效解决研究和创新问题的潜力。公民科学方法有其自身的挑战，需要加以考虑以实现这一目标并促进更广泛和更深入的公众参与。然而，讨论在让公众和其他利益相关者参与科学方面所吸取的经验教训的项目评估很少见。为了解决这一差距，我们介绍了 H2020 资助的 DITOs 项目，并讨论了逻辑模型在公民科学中的使用。我们分享了该项目的假设、更深入参与的设计考虑因素及其影响途径，展示了如何在公民科学中利用逻辑模型来监测项目的有效性并使其成功实施。我们希望这项工作将激励公民科学从业者使用类似的工具，并通过这样做来分享他们的经验和潜在的障碍。这些知识对于改善公民科学目前的实践方式及其对科学和社会的影响至关重要。