DeSci EDU: course design and self-perceived evaluation in decentralized science education

Introduction Decentralized science (DeSci) aims to address structural inefficiencies in traditional research yet lacks formal educational pathways. Methods This exploratory case study develops and evaluates an eight-week blended course, DeSci EDU, which combines theory-based seminars, scaffolded assignments, and alumni mentorship. Thirty-two participants completed pre-course self-assessments across ten blockchain and DeSci domains; 22 provided post-course data, and 11 supplied matched identifiers. Results Cohort means increased by 41% for blockchain and 53% for DeSci, with the largest relative gains in governance mechanisms and token-based incentives. Matched-pair analysis showed comparable improvements (+51% and +58%). Discussion The early-career, highly educated sample and reliance on self-report limit generalizability and causal attribution. Nonetheless, the results suggest that a structured practice-oriented curriculum can quickly enhance DeSci literacy. Future iterations should integrate objective performance tasks, transversal competencies, and automated participant tracking to enable scalable and rigorous evaluation.