Look for
Close this search box.

Proposal and validation of an AI-based framework for the personalization of programming learning for beginning university students

General Objective: Develop a framework based on generative AI to personalize a programming learning plan and teaching materials, considering the student's knowledge, their learning style and their interaction with the system, to improve their programming skills and the level of acceptance of teaching materials.

Specific objectives:

  • Analyze and adapt a framework to personalize programming learning routes and teaching materials considering the student's knowledge, learning style, and interaction with the system.
  • Create the data set necessary to instantiate the programming learning paths and teaching materials customization framework.
  • Select an appropriate generative AI model for the personalization of learning paths and programming teaching materials.
  • Adapt the selected generative AI model to personalize programming learning routes and teaching materials, considering the student's knowledge, learning style, and interaction with the system.
  • Validate the implemented model by evaluating the improvement of students' skills and the level of acceptance of the teaching materials.

Participating Institutions:

EPN, ESPE, UDLA, YACHAY

Project Director Danny Santiago Guamán Loachamín

Participants:

  • Julio César Caiza Ñacato
  • José David Vega Sánchez
  • Karina Lorena Cela Rosero
  • Aída Noemí Bedón Bedón
  • Angel Gabriel Jaramillo Alcázar
  • William Eduardo Villegas Chiliquinga
  • Jefferson Alexander Moreno Guaicha
  • Franklin Leonel Sánchez Catota

Awarded budget: $38,673.60

Project Status: Awarded