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Abstract: Over the last decade, the technology advancements were quickly absorbed and integrated into education processes and eLearning which enabled the development of efficient and innovative solutions able to act as customer tailored learning resources. One of the most ground-breaking innovations in the eLearning field is the integration of Chatbots technology into teaching experience, which acts as an intelligent bridge between education and technology. Chatbots technology can be used in a wide spectrum of fields due to its flexibility and ability to adapt to the pace at which each individual feels comfortable, without causing overwhelming or exhaustion. This paper aims to blend e-Assisted learning and communication into classrooms, introducing Chatbots as real-time educational assistants for the teacher - they are designed to distribute interactivity with students and to manage it at individualized level. This approach adds a highly increased degree of interactivity and personalization to the learning experience, aspects which are critical from the student point of view as each individual has its own learning and understanding capabilities. The authors combined modern software technologies such as Cloud based development, micro-services, Java technologies and Chatbots to create an automated closed loop for the teaching pace and adaptive complexity in a classroom. The proposed solution avoids putting the teacher in a secondary position, shadowed by technology - it rather empowers him with e-Assistants that give him access to a real time and relevant statistic of individual students' understanding level - a valuable feedback for personalized education which leads to an improved mentorship quality.
Keywords: Machine learning; e-Assisted teaching; blended learning; chatbots; micro- services; real time understanding individualized assessment.
I.INTRODUCTION
"Education 4.0" [1] integrates the innovative technologies of artificial intelligence (AI) in the blended learning (as a combination of individualized e-Learning with traditional classroom methods). After the proliferation of distance learning platforms, collaborative labs and online tests of "Education 3.0" (the e-Learning), time has come for Machine learning (m-Learning) to support adaptive and selfdirected education. Our research is using mobile "thin clients" (tablets or smartphones), aiming to innovate the learning/communication process in the classroom with the help of Chatbots. The individual mobile terminals of the students are connected to the lessons repository in the educational Cloud of the university, in a dynamic relationship where the Chatbots were implemented...