IDEAS home Printed from https://ideas.repec.org/a/dbk/rlatia/v1y2023ip8id1062486latia20238.html
   My bibliography  Save this article

Smart Tutors: improving the quality of higher education through AI

Author

Listed:
  • Dalía Rodríguez Cairo
  • Yisel Ramírez Echavarría

Abstract

Intelligent Tutoring Systems (ITS) are revolutionizing higher education through artificial intelligence (AI), offering personalized and adaptive learning experiences. In this sense, the study aimed to analyze the impact of ITS on the quality of higher education based on AI. For this purpose, a bibliographic review was carried out that explored the main trends around the current topic. Among the findings, it was recognized that ITS use advanced algorithms, such as data mining and Bayesian networks, which allow educational content to be dynamically adjusted to meet the individual needs of students, improving learning effectiveness and keeping students more engaged and motivated. . This integration was shown to significantly improve knowledge retention and reduce dropout rates through real-time, personalized interventions. In addition, a focus on the sustainability and scalability of these systems was evident, integrating sustainable design principles. These developments made it possible to ensure that intelligent tutors can be widely implemented in various educational institutions without losing their effectiveness, thus improving the quality of higher education in a sustainable and expansive manner.

Suggested Citation

Handle: RePEc:dbk:rlatia:v:1:y:2023:i::p:8:id:1062486latia20238
DOI: 10.62486/latia20238
as

Download full text from publisher

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a
for a similarly titled item that would be available.

More about this item

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dbk:rlatia:v:1:y:2023:i::p:8:id:1062486latia20238. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Javier Gonzalez-Argote (email available below). General contact details of provider: https://latia.ageditor.uy/ .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.