Though only a dream a while ago, artificial intelligence (AI) has become a reality, being now part of our routines and penetrating every aspect of our lives, including education. It is still a field in its infancy, but as time progresses, we will witness how AI evolves and explore its untapped potential. Against this background, this chapter examines current insights and future perspectives of AI in various contexts, such as natural language processing (NLP), machine learning, and deep learning. For this purpose, social network analysis (SNA) is used as a guide for the interpretation of the key concepts in AI research from an educational perspective. The research identified three broad themes: (1) adaptive learning, personalization and learning styles, (2) expert systems and intelligent tutoring systems, and (3) AI as a future component of educational processes.
Abstract-The purpose of this study was to investigate whether a sense of community could be enhanced via learning activities delivered through a Facebook group within a self-paced distance-learning course. A closed Facebook group was created for a voluntary English as a foreign language course. Four types of learning activities were delivered via the Facebook group including both synchronous and asynchronous structured activities, and synchronous and asynchronous unstructured activities. The study was designed as convergent mixed-method study. Quantitative data were gathered from a total of 179 students by using the Classroom Community Scale; quantitative data were concurrently gathered from 17 students via semi-structured interviews. The results revealed that the sense of community among learners was found to be high, however, the type of learning activities had no effect on building a sense of community. The study was intended to guide teachers, instructors, administrators and practitioners interested in designing and delivering self-paced open and distance learning courses.
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