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Unlocking long-term engagement with citizen science: communication strategies driven by complex thinking under an AI-assisted approach
(2023-10-25) Sanabria Zepeda, Jorge Carlos; Artemova, Inna; Argüelles Cruz, Amadeo José; Olivo Montaño, Pamela Geraldine; https://ror.org/03ayjn504; https://ror.org/043xj7k26; https://ror.org/059sp8j34; https://ror.org/00prsav78
Citizen science projects continue to grow in popularity and diversity of modalities, with an ever-increasing scope. In addition, these projects allow the development of participants' complex thinking competency. However, their involvement is mostly limited to crowdsourcing tasks, resulting in short periods of participation, which are associated with low motivation. This article seeks to present communication strategies to sustain participant long-term engagement, to be applied by citizen science project stakeholders while considering complex thinking as a driver. The methodology used was Cognitive Task Analysis methodology and utilized the Think-Aloud Protocol method, where the authors themselves are actively involved in the study, and AI-assisted. After multiple iterations between the authors and the AI assistant, the following findings were reached: a) effective communication necessitates clear articulation of goals, bridging the gap between scientific language and layperson understanding, fostering ownership and co-creation; b) the critical analysis of ChatGPT results encompassed factors such as educational and professional backgrounds, multidisciplinary involvement, and technical issues, creating an ideal setting for fostering discussions, constructive work, critical thinking, and knowledge enrichment; c) the process of using ChatGPT for the design of strategies motivated various sub-competencies of complex thinking, to achieve comprehensive results.

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