The utilization of self-regulated learning (SRL) requires enacting complex and cyclical cognitive, affective, metacognitive, motivational, and social processes that may be influenced by individual differences such as personality. The frequency and types of SRL strategies enacted by learners are impacted by individual differences (e.g., motivation orientation, demographics), however current literature has yet to fully examine the influence of learners’ personality traits on SRL processes and learning outcomes while using intelligent tutoring systems (ITSs). In this study, we investigated the relationship between undergraduate students’ (N = 110) personality traits and their SRL processes and learning outcomes while using MetaTutor, an ITS designed to provide adaptive scaffolding while learning about the human circulatory system. Results indicated significant differences in participants’ learning outcomes across different personality clusters, as well as differences in the use of note taking, an effective SRL strategy predictive of learning gains. However, there was not a significant interaction or effect on the combination of SRL engagement, learning outcomes, and personality clusters. These results highlight the importance of individual differences in understanding how personality traits influence students’ self-regulation and strategy use with ITSs during complex learning. Future ITSs can leverage personality traits through a comprehensive multimodal integration approach that begins with sophisticated assessment methods combining personality inventories, self-reports, and trace data to adapt their content delivery, feedback and scaffolding methods, based on personality traits and other individual differences.