Exploration of Knowledge Engineering Paradigms for Smart Education: Techniques, Tools, Benefits and Challenges

Abstract

Knowledge engineering paradigms (KEPs) deal with the development of intelligent systems in which reasoning and knowledge play pivotal role. Recently, KEPs receive increasing attention within the fields of smart education. Researchers have been used the knowledge engineering (KE) techniques, approaches and methodologies to develop a smart tutoring systems (STSs). The main characteristics of such systems are the ability of reasoning, inference and based on static and heuristic knowledge. On the other side, the convergence of artificial intelligence (AI), web science (WS) and data science (DS) is enabling the creation of a new generation of web-based smart systems for all educational and learning tasks. This paper discusses the KEPs techniques and tools for developing the smart educational and learning systems. Four most popular paradigms are discussed and analyzed namely; case-based reasoning, ontological engineering, data mining and intelligent agents. The main objective of this study is to determine and exploration the benefits and advantages of such computational paradigms to increase the effectiveness and enhancing the efficiency of the smart tutoring systems. Moreover, the paper addresses the challenges faced by the application developers and knowledge engineers in developing and deploying such systems. In addition to institutional and organizational aspects of smart educational technologies development and application