Background: Previous research has shown that teachers hold misconceptions about multimedia learning (e.g., multimedia instruction needs to be adapted to students' learning styles), which may be at odds with evidence-based teaching. Objectives: Refutation texts are a classical method to reduce misconceptions and thus to stimulate conceptual change. We wanted to know whether making use of a computer algorithm to personalize refutation texts would best initiate teachers' conceptual change. Methods: We designed an online experiment, in which N = 129 in-service teachers read either (1) expository texts (without direct refutation), (2) common refutation texts, or (3) personalized refutation texts. The teachers filled in a misconception questionnaire pre and post to assess their conceptual change. Results and Conclusions: Statistical analyses revealed that personalized refutation texts initiated the strongest conceptual change, which was driven by increased feelings of guilt and shame. Common refutation texts did not foster teachers' conceptual change as compared to expository texts. These findings indicate that refutation texts should be personalized for experienced practitioners such as teachers. Takeaways: Personalized refutation seems to be promising in the context of online teacher training programs. Further research should test to which extent the present findings also apply to other groups of experienced learners or practitioners.