Background: Over the last 20 years, educational large-scale assessments have undergone dramatic changes moving away from simple paper-pencil assessments to innovative, technology-based assessments. This comprehensive switch has led to some rather technical improvements such as identifying early guessing or improving standardization. Objectives: At the same time, process data on student interaction with items has been shown to carry value for obtaining, reporting, and interpreting additional results on student skills in international comparisons. In fact, on the basis of innovative simulated assessment environments, news about student rankings, under- and overperforming countries, and novel ideas on how to improve educational systems are prominently featured in the media. At the same time, few of these efforts have been used in a sustainable way to create new knowledge (i.e., on a scientific level), to improve learning and instruction (i.e., on a practical level), and to provide actionable advice to political stakeholders (i.e., on a policy level). Methods: This paper will adopt a meta-perspective and discuss recent and current developments with a focus on these three perspectives. There will be a particular emphasis on new assessment environments that have been recently employed in large-scale assessments. Results and Conclusions: Most findings remain very task specific. We propose necessary steps that need to be taken in order to yield sustainable change from analysing process data on all three levels. Implications: New technologies might be capable of contributing to the research-policy-practitioner gap when it comes to utilizing the results from large-scale assessments to increase the quality of education around the globe but this will require a more systematic approach towards researching them.