Human-Computer Interaction

You are here

Credits
4.5
Department
CS
Types
Elective
Requirements
This subject has not requirements
The main objective of this course is to provide the students with a wide understanding of the state of the art in human computing interaction concepts. Perception and cognition topics are esential to design interactive systems. Special attention will be paid on pervasive computing and Ambient Intelligence where the central object of study are people surrounded by intelligent systems and enhanced environments capable to monitorize and/or interact in a user friendly way. The user-centered design methodology will be the most used throughout the course.

Teachers

Person in charge

  • Joan Cabestany Moncusi ( )

Others

  • Andreu Catala Mallofre ( )

Weekly hours

Theory
0.5
Problems
0
Laboratory
1.3
Guided learning
0.5
Autonomous learning
1

Competences

Technical Competences of each Specialization

Academic

  • CEA10 - Capability to understand advanced techniques of Human-Computer Interaction, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.

Professional

  • CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
  • CEP4 - Capability to design, write and report about computer science projects in the specific area of ??Artificial Intelligence.
  • CEP6 - Capability to assimilate and integrate the changing economic, social and technological environment to the objectives and procedures of informatic work in intelligent systems.
  • CEP7 - Capability to respect the legal rules and deontology in professional practice.

Generic Technical Competences

Generic

  • CG1 - Capability to plan, design and implement products, processes, services and facilities in all areas of Artificial Intelligence.
  • CG3 - Capacity for modeling, calculation, simulation, development and implementation in technology and company engineering centers, particularly in research, development and innovation in all areas related to Artificial Intelligence.

Transversal Competences

Teamwork

  • CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.

Appropiate attitude towards work

  • CT5 - Capability to be motivated for professional development, to meet new challenges and for continuous improvement. Capability to work in situations with lack of information.

Analisis y sintesis

  • CT7 - Capability to analyze and solve complex technical problems.

Objectives

  1. Acquiring Human-Computer Interaction general methodology
    Related competences: CT3, CEA10, CEP3,
  2. Development of Ambient Inteligence related projects
    Related competences: CT3, CT5, CT7, CEA10, CEP3, CEP4, CEP6, CEP7, CG1, CG3,

Contents

  1. Introduction
    Principles of human-computer interaction.
    User centered design, user needs elicitation and ergonomics principles.
    Contexts of use, and functional requirements.
    User-system communication design.
  2. Interaction
    Principles of human information processing, performance, learning and cognition.
    Sensation and perception.
    Cognitive basis of emotions. Cognitive engineering.
    Multimodal interaction.
  3. Pervasive Computing
    Principles and technology overview.
    Architectures.
    Operating Systems.
    Location and context awareness.
    Ubiquitius interfaces.
  4. Person centered Ambient Intelligence
    Smart environments. Principles and technologies of Ambient Intelligent design.
    Ambient Assisted Living (AAL): requirements and solutions.
    Ethics in AAL: privacy, autonomy, integrity, reliability, e-inclusion, technology in the society,…

Activities

Introduction

Theory
1.5
Problems
0
Laboratory
4
Guided learning
0
Autonomous learning
3
Objectives: 1
Contents:

Interaction

Theory
1.5
Problems
0
Laboratory
4
Guided learning
0
Autonomous learning
3
Objectives: 1
Contents:

Pervasive Computing

Theory
1.5
Problems
0
Laboratory
4
Guided learning
0
Autonomous learning
3

Person centered Ambient Intelligence

Theory
1.5
Problems
0
Laboratory
4
Guided learning
0
Autonomous learning
3

Ambient Intelligence Project

Theory
2
Problems
0
Laboratory
6.5
Guided learning
8
Autonomous learning
2
Objectives: 2

Teaching methodology

The subject will follow a Project Based Learning approach:
1.The student should do a literature review of the field, detecting the most important research groups, patents and projects in his area of interest
2.Design of a real intelligent environment based on a use case
3.Detailed analysis of the architecture and algorithmia.
4.New technologies and innovative aspects of the proposed solution

Evaluation methodology

The evaluation fundamentally is based on the degree and level of participation of the student throughout the course in the sessions of class (contribution to the debate of the subjects, exposition and resolution of questions...), and in the development, conclusions and presentation of its works of practices. A midterm and final test will also contribute to the subject assessment. A midterm and final test will also contribute to the subject assessment

Previous capacities

None