Pedagogical agents (PAs) have the ability to scaffold and regulate students' learning about complex topics while using intelligent tutoring systems (ITSs). Research on ITSs predominantly focuses on the impact that these systems have on overall learning, while the specific components of human-ITS interaction, such as student-PA dialogue within the system, are given little attention. One hundred undergraduate students interacted with MetaTutor, a multiagent hypermedia ITS, to learn about the human circulatory system. Data from these interactions were drawn from questionnaires and log-files to determine the extent to which a specific agent from MetaTutor, Sam the Strategizer, impacted students' overall emotions while using the system. Results indicated that Sam negatively impacted students' experiences of enjoyment, in relation to the other agents of MetaTutor, and the frequency of Sam's interactions with students significantly predicted their reports of boredom while using the system. Implications for the design of affect-sensitive multiagent ITSs are discussed.