The engineering education system has been in dire need of reform for the past five years to meet the demands of society in the 6G era. AI intervention and the Internet of Things are paving the path to success in the smart engineering education system. Still, students entering professional courses are facing challenges in addressing the correlation of basic sciences with engineering course outcomes. In view of the impending educational revolution brought about by deep learning in the basic sciences, it is critical to understand how this development will influence current pedagogical practices to design and implement long-term AI solutions for engineering education. One potential solution is to make our classrooms more collaborative spaces where students and teachers work together to achieve positive learning outcomes using artificial intelligence in the 6G era. The main purpose of this research is to examine how artificial intelligence (AI) intervention in basic sciences changes education in areas such as intelligent tutoring systems, AI-powered collaborative learning, AI-powered automated assessment, and AI-powered customized learning. In this study cluster and multistage sampling techniques were used for sample size 1000. The data set consists of students, alumni as employers and employees of different places irrespective of educational institutions. The results of action plan implementation and conceptual activities emphasizing real-time applications with and without AI intervention were analyzed by standard deviation and linear regression analysis. In addition to the improvised engagement and retention rates of aspiring engineers, the present study incorporates the ongoing endeavors to improve instructional methods, embrace technological advances, and tackle inclusive challenges to guarantee AI intervention in basic sciences education.
Author
(s) Details
K.S. Rudramamba
Department of Physics, VNR Vignana Jyothi Institute of Engineering and
Technology, Hyderabad-500090, Telangana, India.
Please see the book
here:- https://doi.org/10.9734/bpi/mono/978-93-48859-10-5/CH17
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