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Metadata
  • Id: EU.AI4T.O1.M2.2.5t
  • Title: 2.2.5 What types of AI applications in Education
  • Type: text
  • Description: The existing AI systems, their potential or existing uses in Education
  • Subject: Artificial Intelligence for and by Teachers
  • Authors:
    • AI4T
  • Licence: CC BY 4.0
  • Date: 2022-11-15

What types of AI applications in Education

Among the possible classifications of AI scientific domains, the following table presents an AI taxonomy1 according to the family functions possibly performed by AI.

   Image of AI Taxonomy  

Figure: AI taxonomy - AI scientific domains and subdomains (from Samoili & al., 2021 JRC report1).

Let's see which AI techniques are used in the AI-based education-oriented applications proposed by Holmes & al. in 20192.

   Image of AI-based education-oriented systems 

Figure: Different types of current AI-based systems for Education (from Holmes & al. 20192).

Each AI-based educational tool or resource has its own specific techniques. However, it is sometimes possible to guess which ones are likely to be used for a given resource.

Let's take some examples:

  • Dialogue-based tutoring system, as a student teaching service Such systems are likely to use: communication techniques such as natural language processing for speech and language understanding and generation and reasoning techniques for tutoring purposes

  • Course recommendation, as a student supporting service As for personalised marketing offers and recommendations functions that can be found on the Internet, course recommendation systems are probably based on machine learning techniques by analysing relevant current data related to the student learning path and identifying similarities to previous generalised student learning paths.

  • Student attention and emotion detection, as a teacher supporting service Such a system is likely to use perception techniques (computer vision for facial recognition for example) and machine learning techniques to analyse the student's facial expressions or behaviour if such information are collected and analysed.

  1. AI Watch - Defining Artificial Intelligence - 2.0. Towards an operational definition and taxonomy for the AI landscape - Samoili, S., López Cobo, M., Delipetrev, B., Martínez-Plumed, F., Gómez, E., and De Prato, G. - EUR 30873 EN, Publications Office of the European Union, Luxembourg, 2021, ISBN 978-92-76-42648-6, doi:10.2760/019901, JRC126426. ↩↩

  2. Artificial Intelligence In Education: Promises and Implications for Teaching and Learning - Wayne Holmes, Maya Bialik, Charles Fadel - Boston, MA, Center for Curriculum Redesign, 2019. ↩↩