Checking date: 17/05/2022

Course: 2022/2023

AI in Education
Study: M. Applied Artificial Intelligence (378)

Coordinating teacher: MUÑOZ MERINO, PEDRO JOSE

Department assigned to the subject: Department of Telematic Engineering

Type: Electives
ECTS Credits: 3.0 ECTS


- Know the main applications that use data and artificial intelligence in education. - Know how to use methods to infer intelligent information about students based on their interactions in learning platforms. - Know how adaptive learning applications work. - Know how predictive systems in education work. - Know how to evaluate educational systems.
Skills and learning outcomes
Description of contents: programme
1.- Introduction to learning analytics and applications in education of the use of data 2.- User models 2.1.- Skill models, meta-cognitive models, and affective models 2.2.- Models based on knowledge engineering 2.3.- Models based on probabilistic methods 2.4.- Models based on ontologies 2.5.- Models based on text mining 3.- Adaptative learning 3.1.- Components of an adaptive system 3.2.- Adaptation methods 4.- Predictive systems in education 4.1.- Purposes 4.2.- Methods: regression, random forest, neural networks, etc. 4.3.- Validation and evaluation of the models 5. Evaluation of learning systems 5.1.- Pattern discovery with clustering techniques 5.2.- Comparison between systems or system vs human tutor 5.3.- Evaluation of usability 5.4.- Evaluation of effectiveness and impact 5.5.- Evaluation of other indicators
Learning activities and methodology
- Theoretical sessions - Practical sessions - Office hours - Work in group - Individual work of the student - Final exam
Assessment System
  • % end-of-term-examination 30
  • % of continuous assessment (assigments, laboratory, practicals...) 70
Calendar of Continuous assessment

The course syllabus may change due academic events or other reasons.