Because human performance and reliability can be significantly affected by interface environments, it is required to collect data on the effects of digital systems on human reliability. In this paper, we describe an expert elicitation process to obtain prior knowledge regarding the effects of performance shaping factors on human error probabilities in cognitive failure modes. Based on the classical model of expert elicitation, we estimated the performance shaping factor (PSF) multipliers. For this study, twelve experts experienced in operations or human performance reviews in APR1400 were recruited from four different types of organizations. The experts were asked to predict human error probabilities in APR1400 control rooms for the failure modes and provide estimates for the PSF multipliers. The obtained estimates were aggregated by the classical model method to generate representative values and their uncertainties. In a future study, we plan to collect empirical data from APR1400 simulators and combine them with the aggregated expert opinions to generate robust PSF effect estimates.