Education researchers’ concerns on data and material sharing: A latent class analysis

Special Education and Education researchers tend to support data and material sharing in principle, but actual rates of sharing remain low (e.g., Logan et al., 2025; Cook et al., 2023). The current study used latent class analysis (LCA) to identify distinct groups of education researchers based on their concerns related to sharing data and study materials. We analyzed survey responses from 1,383 education researchers across four sub-samples: those who did and did not share data, and those who did and did not share materials in their most recent scholarly work. Among the respondents who did not share data (Data Non-Sharers; DNS), we found four classes (Unconvinced DNS, Unconcerned DNS, Protective and Possessive DNS, and Overwhelmed DNS). For the respondents who did not share materials (Material Non-Sharers; MNS), we found three classes (Unconcerned MNS, Logistically/Ethically Concerned MNS, and Unconvinced MNS). Class membership was associated with sharing attitudes, behaviors, and future intentions to share. Taken together, these findings suggest that barriers and concerns related to sharing cluster into distinct patterns, which may call for tailored supports.