Smart University is an emerging and rapidly growing area that represents a creative integration of smart technologies, smart features, smart software and hardware systems, smart pedagogy, smart curricula, smart learning and academic analytics, and various branches of computer science and computer engineering. This is the main reason that in June of 2013, a group of enthusiastic and visionary scholars from all over the world arrived with the idea to organise a new professional event and community that would provide an excellent opportunity for faculty, scholars, Ph.D. students, administrators and practitioners to propose and evaluate innovative ideas and approaches, collaborate on design and development of new systems and technologies, and discuss findings and outcomes of research, development, case studies and best practices in Smart Education, Smart e-Learning, Smart University and related areas. The research, design and development topics of our interest in those areas include but are not limited to (1) conceptual modelling of Smart Education, Smart e-Learning, Smart Universities, Smart Campuses, Smart Analytics; (2) infrastructure, main characteristics, functions and features of Smart Universities, Smart Campuses and Smart Classrooms; (3) Smart University-wide software, hardware, security, safety, communication, collaboration and management systems; (4) Smart Education and Smart e-Learning strategies, approaches and environments; (5) Smart Pedagogy; (6) Smart Learning Analytics and Smart Academic Analytics; (7) modelling of Smart Student/Learner and Smart Faculty; (8) assessment and quality assurance in Smart Education and Smart e-Learning; (9) professional development in Smart Education and Smart e-Learning; (10) social, cultural and ethical dimensions and challenges of Smart Education; and (11) educational applications of various innovative smart technologies such as Internet of Things, cloud computing, ambient intelligence, smart agents, sensors, wireless sensor networks and context awareness technology, and numerous other topics. Since that initial meeting in 2013, the following books were published as the logical outcomes of a mutually beneficial collaboration between experts in
Abstract-The multilevel interactions between a mentor and her/his learner could exchange various conceptions between them that are supported by their own conceptualisations. Producing the own realisation of a world and developing it in the context of interactions could be said to be the most valuable product of the constructivist interactions. The most significant matter in meaning construction is producing the own meaningful comprehension, realisation and understanding. Here the learner gets to know how to develop her/his thinking. In this research, I will focus on relating (i) meaning construction through the lenses of the learner's conceptions and (ii) meaning construction through the lenses of constructivism. Constructivism is an educational theory of learning and a model of knowing. The main contribution of this research is analysing the symmetrical relationship between learner and mentor. I will analyse the logical dependencies between learner and mentor and will check their reflectional symmetrical relationship in a conceptual mirror. The conceptual mirror is a phenomenon that represents the meeting point of the mentor's and the learner's conceptual knowledge.
Cognitive, or knowledge, agents, who are in some way aware of describing their own view of the world (based on their mental concepts), need to become concerned with the expressions of their own conceptions. My main supposition is that agents’ conceptions are mainly expressed in the form of linguistic expressions that are spoken, written, and represented based on e.g. letters, numbers, or symbols. This research especially focuses on symbolic conceptions (that are agents’ conceptions that are manifested in the form of their symbols). I attempt to logically (and using CLSYM) analyse symbolic conceptions in terminological systems. CLSYM is an assertional fragment of my developed Conception Language (CL), which is utilised as a formal-logical system for representing and explicating agents’ conceptions of the world.
Abstract. The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. In order to make a linkage between 'Logic' and 'Cognition', Description Logics (DLs) will be employed to provide a logical description and analysis of actual human inductive reasoning (and learning). This research connects with the topics 'logic & learning', 'cognitive modelling', and 'terminological knowledge representation'.
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