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.
Karyotaki et al. (Fri,) studied this question.