During the COVID-19 pandemic, the corporate online training sector has increased exponentially and online course providers had to implement innovative solutions to be more efficient and provide a satisfactory service. This paper considers a real case study in implementing a chatbot, which answers frequently asked questions from learners on an Italian e-learning platform that provides workplace safety courses to several business customers. Having to respond quickly to the increase in the courses activated, the company decided to develop a chatbot using a cloud-based service currently available on the market. These services are based on Natural Language Understanding (NLU) engines, which deal with identifying information such as entities and intentions from the sentences provided as input. To integrate a chatbot in an e-learning platform, we studied the performance of the intent recognition task of the major NLU platforms available on the market with an in-depth comparison, using an Italian dataset provided by the owner of the e-learning platform. We focused on intent recognition, carried out several experiments and evaluated performance in terms of F-score, error rate, response time, and robustness of all the services selected. The chatbot is currently in production, therefore we present a description of the system implemented and its results on the original users’ requests.

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Artificial Intelligence and Natural Language Processing techniques can have a very significant impact on the e-learning sector, with the introduction of chatbots, automatic correctors, or scoring systems. However, integrating such technologies into the business environment in an effective way is not a trivial operation, and it not only requires realising a model with good predictive performance, but also it requires the following: (i) a proper study of the task, (ii) a data collection process, (iii) a real-world evaluation of its utility. Moreover, it is also very important to build an entire IT infrastructure that connects the AI system with the company database, with the human employees, the users, etc. In this work, we present a real-world system, based on the state-of-the-art BERT model, which implements an automatic scoring system for open-ended questions written in Italian. More specifically, these questions pertain to the workplace safety courses which every worker must attend by law, often via e-learning platforms such as the one offered by Mega Italia Media. This article describes how our system has been designed, evaluated, and finally deployed for commercial use with complete integration with the other services provided by the company.