Methodology for the Implementation of Virtual Assistants for Education Using Google Dialogflow
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© Springer Nature Switzerland AG 2019.We developed a virtual assistant that enables students to access interactive content adapted for an introductory undergraduate course on artificial intelligence. This chatbot is able to show answers to frequently asked questions in a hierarchical structured manner, leading students by either voice, text or tactile input to the content that better solves their questions and doubts. It was developed using Google Dialogflow as a simple way to generate and train a natural language model. Another convenience of this platform is its ability to collect usage data that is potentially useful for lecturers as learning indicators. The main purpose of this paper is to outline the methodology that guided our implementation so that it can be reproduced in different educational contexts and study chatbots as tools for learning. At the moment, several articles, news and blogs are writing about the potential, implementation and impact chatbots have in general contexts, however there is little to no literature proposing a methodology to reproduce them for educational purposes. In that respect, we developed four main categories as a generic structure of course content and focused on quick implementation, easy updating and generalization. The final product received a general approbation of the students due to its accessibility and well structured data.