Journal of Theoretical and Applied Information Technology 31 st October 2022. Vol.100. No 20 © 2022 Little Lion Scientific ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 6020 CHATBOT-SUPPORTED SMART LEARNING: ALGORITHMS AND IMPLEMENTATION 1 DALIA KHAIRY , 2 MARWA F. AREED ,* 1 MOHAMED A. AMASHA, 1 3 SALEM ALKHALAF, , 1 RANIA A. ABOUGALALA 1 1 Faculty of Specific Education, Computer Teacher Preparation Dept., Damietta University, Damietta, Egypt . 2 Faculty of Engineering, department of computer science, Damietta University, Damietta, Egypt. . 3 Faculty of Science and Arts, Computer Science Department, Qassim University, Alrass, Saudi Arabia. E-mail: 1 shamaamora2014@gmail.com, , 2 Marwa_Areed@du.edu.eg , 1 mw_amasha@yahoo.com , 3 s.alkhalaf@qu.edu.sa , 1 Ronyabogalala@hotmail.com ABSTRACT Recently, increasing numbers of chatbots have been used in diverse fields, using various languages and technologies. Designing an interactive smart chatbot based on query-response systems in education has emerged as an important challenge in managing online discussion with natural language. This paper presents the SCBHE, which can receive queries from students and deliver responses about educational and administrative support to improve communication and services while decreasing the huge workload in universities. The SCBHE depends on identifying students’ intents and extracting contextual information to deliver appropriate responses to students’ queries, the framework will assist with decreasing the work burden, as educators will no longer need to repeatedly answer the same questions and explain the same points to various students. The SCBHE was built based on Dialogflow, an artificial intelligence tool introduced by Google. The chatbot was developed using an algorithm with the eight following phases: GUI development, acquisition, preprocessing, extraction, response induction, updating, awareness , and authentication. In this study, handling the SCBHE context information is limited to implementing the first five phases of the proposed algorithm. Keywords: Educational Robotics, Artificial Intelligence, Context-aware Technology, E-learning. Abbreviations SCBHE: Smart Chatbot for Higher Education GUI: Graphical User Interface 1. INTRODUCTION A good higher education establishment is not only one with profoundly qualified educators, up-to-date and prepared labs, or advanced courses; it is one that offers excellent help to its students. Most students who exit college before completing their studies do so because of poor support (Okonkwo & Ade-Ibijola, 2021). Therefore, it is important for each institution to continuously direct their students by giving them accurate information that they can access conveniently as a form of support. Yet, it is difficult to ensure that every undergraduate is being appropriately supported in a practical sense (Mutovkina, 2020). In contrast, we observe every day that many students either search online for help with their tasks or search for fast responses regarding the courses they are taking, campus updates, admissions, faculty, and so on. Similarly, educators require some efficient options because approaches they currently use to support students are time-consuming (Venusamy & Basha, 2021). A chatbot can make the difference for productively searching for information. There is no need to manually search for simple answers that the institution can set up for their chatbot once, and which will then be accessible for as long as necessary. A chatbot can help students find information on topics from class updates to task accommodation cutoff times. What is more, educators can profit from a chatbot in numerous ways to work in order to save time and effort during sending responses for their students; in addition,