Learning tax regulations through rules-based chatbots using decision trees: a case study at the time of COVID-19

• Published in: 2020 39th International Conference of the Chilean Computer Science Society (SCCC) pp. 1 - 8
• Main Authors: Mellado-Silva, Rafael, Faundez-Ugalde, Antonio, Lobos, Maria Blanco
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.11.2020
• Subjects: chatbot; COVID-19; decision tree; tax learning
• DOI: 10.1109/SCCC51225.2020.9281267

Chatbots have represented a revolution in how companies relate internally to their collaborators and externally to their customers. The impact they have had is directly related to saving time in business processes, an improvement in experience, and economic savings for those who implement them. At the educational level, various experiences of virtual assistants have been appreciated with promising results about how the tools are exploited against the learning results of the students. This paper presents the experience carried out by accounting students to teach rules related to tax control processes through the use of a rules-based chatbot that uses decision trees. The study focused on remote learning for COVID-19 reasons. The results of this experience are promising in this area, due to the complexity of the content and the little innovation in existing teaching subjects in the area. In general, the students presented an improvement in learning compared to other remote learning techniques.