Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review

Abstract

In the current era, education, like other fields, relies heavily on big data. Moreover, artificial intelligence, including affective computing, is one of the most essential and popular technologies adopted by educational institutions to process and analyze big data. In this systematic review, many previous research types related to improving educational systems using artificial intelligence techniques were studied, such as: deep learning, machine learning, and affective computing. This systematic review aims to identify the gaps in students' emotional understanding in distance education systems. The world has recently witnessed the spread of educational processes for distance learning, especially in the university and the enormous open online courses (MOOCs). Besides, the COVID-19 pandemic has been involved in changing all educational processes to a distance learning system. The results indicated that these systems recorded a high success rate. However, the teacher does not fully understand the student’s emotional state during the educational session. It also lacks monitoring or monitoring during the electronic exams, which are electronic exams. So, it is a widespread problem in distance learning.

Використання Засобів Штучного Інтелекту Для Підтримки Групової Динаміки Проєктних Команд: Вплив На Самоефективність Та Залученість Студентів

“…To achieve the objectives, we relied on the methodological foundations of the literature review process as a research method. For instance, this approach was applied in analysing methods and technologies for supporting group dynamics, as well as in exploring application of artificial intelligence tools in education [20]. Additionally, case study and survey methods [21] were employed to meet the first and second objectives of the study, respectively, involving student participants.…”

From Didachography to AI: Metaphors Teaching is Automated by

“…This appears to be the case with research on AI in education, specifically, which, according to Zawacki-Richter et al (2019), predominantly originates in Computer Science and Engineering departments, with little or no attention paid to pedagogical questions that arise in respect to actual uses of such systems in real educational settings. Other surveys of research output on the topic (e.g., Chassignol et al 2018;Hooshyar, Yousefi & Lim 2019;Guan, Mou & Jiang 2020;Aljarrah et al 2021;Zhai et al 2021;Flores et al 2022) 1 offer consistent claims, shedding further light on the ways in which ideas such as affective computing, natural language processing and facial recognition are being recontextualised to support the development of AI for assumedly educational purposes.…”

Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world

“…It has also turned a crisis into an opportunity, and catalyzed a shift to AI-driven digital teaching/learning (Green et al, 2020 ; Moorhouse, 2020 ). AI has become one of the most essential and popular technologies adopted by university educators to process and analyze big data for distant learners (Aljarrah et al, 2021 ; European Commission, 2022 ). To develop teachers’ competencies to adapt AI-driven teaching and learning tools and approaches, educators need to timely update their skills and knowledge so as to create suitable learning environments for their students (Williamson & Eynon, 2020 ).…”