A Chatterbot Sensitive to Student's Context to Help on Software Engineering Education

Requirements extraction is an important element of the software development process. One of the most used techniques for requirements extraction is the interview. Initiatives to support the training and technical training of computing students in this area are being proposed, such as the development of support mechanisms. These initiatives are proposed by the fact that computing students are graduating with limited practical knowledge in requirements extraction. In parallel, chatterbots have been investigated as tools with the capacity to support the training of students from different areas of knowledge, since the main characteristic is verbal conversational behavior. In medicine, for example, they can take on the role of a sick patient to train students to extract information about the patient's symptoms. One subject that has been explored in the context of educational chatterbots is context awareness, so that the chatterbot can present the right information for the right user. These surveys start from the premise that not every student has the same knowledge as their peers on the subject. Thus, in this research work in full paper we describe a chatterbot that offers support to Software Engineering Education, focusing mainly on the requirements extraction, which assumes the role of a stakeholder. A prototype of a chatterbot that is sensitive to student's context is presented, as well as preliminary results on the impact of this support mechanism in Software Engineering Education.