Learners are faced with the challenge of processing a large amount of knowledge. However, they often lack individual support, and teaching is not tailored to their learning styles. Conversational Agents (CAs) could be a way to identify personal learning styles through a dialog between the CA and the learner, and to support him/her accordingly. This paper investigates whether learning styles can be determined through a dialog with a CA and how the conversation is perceived by users. For this purpose, a CA called Vicky was developed using the platform Rasa and the intent classifier DIET. Vicky determines the user’s learning styles through a questionnaire as well as a quiz and acts human-like to be perceived as a virtual companion. The prototype was evaluated in an experiment with 25 participants. They predominantly perceived themselves to be correctly classified and treated kindly by the CA. Overall, we contribute to science and practice by showing that CAs acting as virtual companions can be used to better understand learner preferences.