Global Trends and Iberoamerican Contributions To The Academic Production of Artificial Intelligence Applied to Engineering Education
Artificial intelligence promises to change the world as we know it, but according to the evidence and the Gartner curve, all technology passes for different stages until it gets the productivity plate which is much less than the initial expectative. Artificial Intelligence has a number of applications in all the fields of knowledge, and it is applied to education since some years ago. Our inters of artificial intelligence is beyond education in general, it is focused on engineering education. This work shows results of a bibliometric analysis enabled for artificial intelligence applied to education engineering, first as a worldwide approach, then `it is focused on the academic production of Iberoamerican countries for the artificial intelligence applied to engineering education. Results show a huge opportunity in this area because there are not so many academic products, they only overcome the 100 publications by year just in 2021, also in the top 20% of producers appear 4 Iberoamerican countries such as Spain, Brazil, Mexico, and Portugal. This is very interesting to remark that Brazil and Mexico are in the top ten worldwide STEM graduates. It’s interesting to notice that while in the top 10 of STEM graduated there are 5 countries members of BRICS and just 3 countries members of G7, the top 10 of countries which produces more academic products related to the artificial intelligence to engineering education are 4 countries members of BRICS and just 3 countries members of G7, tipping the balance in favor of the BRICS. Trends indicate that more than 1,000 products over this topic will be published annually for 2030.
Authors
- Jose-Ignacio Castillo-Velázquez (ORCID: https://orcid.org/0000-0003-4524-8678)
- Rafaela Blanca Silva López (ORCID: https://orcid.org/0000-0002-4978-1130)
Institutions
- Universidad Autónoma Metropolitana (MX)
- Universidad Nacional Autónoma de México (MX)
Publication Details
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1109/colcom62950.2024.10720280
- Citations
- 1
- Primary Topic
- E-Learning and Knowledge Management
- Type
- article
- Field-Weighted Citation Impact
- 0.41