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This study examines the temporal co-occurrences of self-regulated learning (SRL) activities and three types of knowledge (i.e., task information, domain knowledge, and metacognitive knowledge) of 34 medical students who solved two tasks of varying complexity in a computer-simulated environment. Specifically, we explored how task complexity affected the use of SRL activities, types of knowledge, and their interplays using epistemic network analysis (ENA). We also compared the differences between high and low performers. The results showed that the use of SRL activities, especially planning and monitoring, was more intensive in a difficult task compared to an easy task. Students also used more domain knowledge to solve the difficult task. For both tasks, domain knowledge and metacognitive knowledge co-occurred most frequently, followed by domain knowledge and planning. Nevertheless, the interplay of SRL activities and types of knowledge is generally different between the two tasks.