Artificial intelligence in a modernizing science and technology education: a textual narrative synthesis in the COVID-19 era

Abstract

Abstract The COVID-19 pandemic shifted the mode of learning to online. This gave the artificial intelligence (AI) developers the reason to increase its usage and production to every detail of the teaching learning process. This synthesis paper was intended to capture these new technologies in the last five years. Using the textual narrative analysis approach and course design triangle model, this paper looked into the AI integration in the field of science and technology education. A total of 15 studies were analyzed and synthesized coming from different journal hosting platforms such as Google Scholar, ERIC, Elsevier, etc. The results have shown that there is indeed a wider utilization of AI in various aspects of the teaching and learning process. These were seen in the learning activities, presentation translators, marking, feedbacking, predicting average score, and intelligent tutoring system. These AI technologies have proven to positively affect the learning of the students and helped the teachers along the process. Furthermore, there is a need to totally synthesize these AI systems which can be beneficial to a wider technical audience.