[Context and motivation] Due to the increasing complexity of software systems, explainability has become a relevant quality aspect. Since the need for explanation is highly user- and context-dependent, the requirements engineering process of explainability is particularly important. [Question/problem] The elicitation of explanation needs is time-consuming and may be subject to several biases. To mitigate these biases, explanation needs are often elicited by observing users while using the respective system. However, this process is not trivial and depends on detailed insights into user behavior. [Principal ideas/results] Eye tracking data provides precise eye movement visualizations and indicates how long specific points on the screen are focused on, allowing for deeper insights into user behavior. Eye trackers can also provide indications of stress and mental load by monitoring pupil diameter. These insights might support the elicitation of explanation needs. [Contribution] In this paper, we aim to take the first step towards identifying explanation needs using eye tracking data. We provide three key contributions: (1) We demonstrate that eye tracking data supports the manual detection of explanation needs. (2) We identify four gaze patterns that occur during the need for explanation. (3) We determine the amplitude of saccades in combination with gaze patterns as a promising indicator of the need for explanation, paving the way for future research.