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30 Technium Soc. Sci. J. 109 (2022)
Chatbots as Cognitive, Educational, Advisory & Coaching Systems

handle is hein.journals/techssj30 and id is 110 raw text is: Technium Social Sciences Journal Vol. 30, 109-126, April, 2022 ISSN: 2668-7798 SOCIAL SCIENCES JOURNAL www.techniumscience.com Chatbots as Cognitive, Educational, Advisory & Coaching Systems Karyotaki Maria12, Athanasios Drigasi, Charalabos Skianis2 'N.C.S.R. Demokritos, Greece, 2University of the Aegean, Greece mkaryotaki@aegean.gr1 2, dr@iit.demokritos.gr', cskianis@aegean.gr2 Abstract. Chatbots are software applications assimilating human communication with the aim to raise adherence and engagement between human-systems interaction. Text messaging-based conversational agents (CAs) make an interesting use of natural language processing and improve by learning, allowing coherent two-way communication with humans, either oral or written as well as real-time decision-making. Chatbots serve as means of learning and teaching, as virtual assistants and social companions. Machine learning algorithms embedded into Chatbots simulate human cognition, including cognitive learning, decision making and adaptation to the environment. Thus, the future of artificial intelligence in Chatbots lies in the development of a global, reliable and sustainable ecosystem of knowledge, skills and values by bringing together all interested stakeholders, such as scientists, consumers, businesses and the state. Such effective customized/personalized learning frameworks depend on sophisticated conversational flows based on user models, which cluster user preferences and attributes in combination with learning analytics to induce end users' personal skills, knowledge mastery, learning ability as well as professional development. Keywords. Chatbots, Intelligent tutoring systems 1. Introduction In general, the use of Chatbots focuses on marketing tasks or disseminating information about a product. Conversational bots are based on decision trees or driven by artificial intelligence (AI). When their algorithm is implemented in Al systems, they are trained to be able to interpret user input within the conversation, understand the questions and decide what to answer. Their training capability is possible thanks to the processing, comprehension and natural language generation technologies. There are two types of Chatbots according to complexity: a first type of structured or first generation Chatbot, which bases its operation on a set of rules and a second type of generative or second generation Chatbot that uses machine learning, artificial intelligence or other machine learning mechanisms to interact with the user. User experience (UX) is responsible for making the conversation between the Chatbot and the user as natural as possible. User interface (UI) is the component through which the user interacts with the Chatbot, that is, what the user can physically see and hear to follow the conversation. Conversational design is a design language, which is based on human conversations and it is responsible for providing common sense to artificial intelligence. 109

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