Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of International Multidisciplinary Research
Darimis Darimis
Unknown Affiliation
Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Virtual Teachers And Teaching Robots: Transform Innovation Of The Future Of Learning In The Era Of Artificial Intelligence Darimis Darimis; Chairul Anwar; Nasril Nasril; Viviana Lisma Lestari; Akhmad Ramli
Journal of International Multidisciplinary Research Vol. 3 No. 5 (2025): Mei 2025
Publisher : PT. Banjarese Pacific Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62504/jimr1239

Abstract

This research aims to analyze the role of virtual teachers and teaching robots as transformative innovations in learning systems in the era of artificial intelligence (AI). With the development of AI technology, this research focuses on how these two technologies can increase learning effectiveness, personalize education, as well as the challenges and opportunities faced in their implementation. The research method used is a literature study with a qualitative approach, collecting and analyzing data from various sources such as journals, articles and reports related to virtual teachers, teaching robots and the application of AI in education. The research results show that virtual teachers and teaching robots are able to provide adaptive solutions in learning, such as 24/7 service, instant feedback, and a more interactive learning experience. However, its implementation still faces obstacles such as emotional limitations, ethical data use, and infrastructure readiness. This study concludes that this innovation has the potential to revolutionize education, as long as it is supported by appropriate policies, improving the quality of technology, and the readiness of human resources. This research provides recommendations for technology developers, educators and policy makers to optimize the use of AI in learning in the future.
Co-Authors Akhmad Ramli Chairul Anwar Nasril Nasril Viviana Lisma Lestari