A Mixed-method Study on Barriers to the Publication of Research Data in Learning Analytics
Englische Version: This study investigates barriers to research data publication in Learning Analytics (LA) through a mixed-method approach encompassing a Systematic Literature Review (SLR), semi-structured interviews, a global survey, and adaptive workshops. The SLR establishes a foundation by identifying legal, ethical, and resource-related barriers to data publication across disciplines. Findings from the SLR integrate in the subsequent interviews, which reveal cultural and institutional nuances affecting researchers' motivations and capabilities for data sharing. A global survey uncovers a discrepancy between researchers' willingness to share data and their perceived benefits from accessing others' data, highlighting trust issues within the scientific community despite growing support for open data. Adaptive workshops underscore the gap between researchers' recognition of data sharing importance and their practical ability to implement it, with data protection concerns, particularly related to GDPR compliance, emerging as major barriers alongside fears of losing data control. The findings from this study illustrate how barriers to data publication vary by discipline and region, being deeply embedded within cultural and institutional frameworks.