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Emotions are typically viewed as end products, excluding how, when, and why emotions change and its impact on self-regulatory processes and learning with intelligent tutoring systems (ITSs). We applied control-value theory and information processing theory of self-regulated learning (SRL) to examine if changes in emotions predicted quantity and quality of SRL processes and performance when learning with an ITS. We captured 113 undergraduates’ emotions, SRL processes, and performance over time with MetaTutor, an ITS. Analyses revealed changes in emotions predicted SRL process use and accuracy of cognitive strategies. While changes in emotions did not predict performance, our findings suggest an indirect effect of changes in emotions on performance over time. Implications are provided for affect-aware ITSs that foster emotion-regulation skills.