Several student drivers have a high level of stress and may need assistance of a specialist, such as a psychologist, in order to enhance their driving skills or even be able to drive on their own. In this context, it is advantageous that such specialists possess resources to deeply analyze and understand the student reactions when submitted to practical driving activities. The literature already include works focusing on automatic detection of driver stress and methods for assisting motorists in real time. However, there is an open research gap regarding the production of reports and summaries about driving activities that can be useful for students behavior analysis and treatment. To this end, we propose an approach for analyzing and summarizing information about driver stress based on their behavior. The approach is supported by a computational tool that allows to view different types of information about the driver under three perspectives: i) videos of the driving activities; ii) reports of behavior analysis; and iii) summaries of relevant actions. A dataset with videos, heart rate and geographic location of driving activities developed by student drivers was produced. The dataset is initially labeled, then the discrete label values are transformed to continuous values to improve visualization and summarization. The approach was evaluated qualitatively by a psychologist and driving instructors. The proposed approach helps a professional to quickly understand the drivers' profile, interpreting the causes of the drivers' reactions, thus providing more accurate assistance.