Recently, in the commercial and entertainment sectors, we have seen increasing interest in incorporating chatbots into websites and apps, in order to assist customers and clients. In the academic area, chatbots are useful to provide some guidance and information about courses, admission processes and procedures, study programs, and scholarly services. However, these virtual assistants have limited mechanisms to suitably help the teaching and learning process, considering that these mechanisms should be advantageous for all the people involved. In this article, we design a model for developing a chatbot that serves as an extra-school tool to carry out academic and administrative tasks and facilitate communication between middle-school students and academic staff (e.g., teachers, social workers, psychologists, and pedagogues). Our approach is designed to help less tech-savvy people by offering them a familiar environment, using a conversational agent to ease and guide their interactions. The proposed model has been validated by implementing a multi-platform chatbot that provides both textual-based and voice-based communications and uses state-of-the-art technology. The chatbot has been tested with the help of students and teachers from a Mexican middle school, and the evaluation results show that our prototype obtained positive usability and user experience endorsements from such end-users.

Today, social networks are crucial commodities that allow people to share different contents and opinions. In addition to participation, the information shared within social networks makes them attractive, but success is also accompanied by a positive User eXperience (UX). Social networks must offer useful and well-designed user-tools, i.e., sets of widgets that allow interaction among users. To satisfy this requirement, Episodic User eXperience (EUX) yields reactions of users after having interacted with an artifact. Anticipated User eXperience (AUX) grants the designers the capacity to recollect users’ aspirations, assumptions, and needs in the initial development phase of an artifact. In this work, we collect UX perceived in both periods to contrast user expectations and experiences offered on social networks, in order to find elements that could improve the design of user-tools. We arrange a test where participants (N=20) designed prototypes on paper to solve tasks and then did the same tasks on online social networks. Both stages are assessed with the help of AttrakDiff, and then we analyze the results through t-tests. The results we obtained suggest that users are inclined towards pragmatic aspects of their user-tools expectations.

Nowadays, chatbots have become popular tools in such a way that they are used in different sectors like commercial, elderly care, tourism, and education. The COVID-19 pandemic has forced many students and teachers to suspend face-to-face classes. Therefore, schools and governments have found it necessary to continue education remotely, using the resources provided by the Internet. This fact has created a greater interest in educational chatbots, so several projects have been proposed to develop these academic tools, each following its way of implementation and addressing issues from different points of view. This paper presents a proposal for chatbot classification, following the Systematic Mapping Study and an iterative method to review and classify educational chatbots. We also discuss the resulting categories and their characteristics and limitations and possible uses by developers and researchers.