This thesis discusses the way individuals in their role as citizens make trade-offs between open education data attributes. The Dutch government agencies lack of insight in the citizen preferences for open data policy attributes lead them to evaluate and develop their open data policy only from the data provider perspective. In order to address the problem, this research aims to identify the citizens preferences for the open education data policy using the citizens stated choice experiments. The experiment is based on Random Utility Maximization theory, the study infers the citizen preferences of open education data attributes based on their choices for several hypothetical open education data policy. The study combines 4 attributes with 3 attribute levels to create the hypothetical open education data policy: mode of information presentation, number of free engaging hackathon events, number of free citizen data skill training events, and risk of your personal data exposed to the public. The citizens significantly value risk of your personal data exposed to the public and mode of information presentation. Government agencies have limited option if it wants to extend the open education data implementation because citizens reluctance to compromise the data protection attribute. This research is a first attempt to extend citizen stated choice experiment approach for the valuation of citizen preferences in the context of open education data policy. It provides an alternative method for governments to evaluate and develop their open data policy alongside the commonly used government/data provider perspective