Fiches de cours

Experience design


Enseignant(s) :

Huang Jeffrey




As we move towards a design economy, the success of new products, systems and services depend increasingly on the excellence of personal experience.This course introduces students to the notion and practice of experience design (human and artificial design) following a hands-on,studio-based approach


Experience design in practice encompasses the collection, analysis and design of users experiences based on a deep understanding of the context concerned. However, such typical workflow tends to be labor-intensive, time-consuming and limited (or biased) given the small datasets used. We will automate these processes algorithmically using crowd-sourced datasets and machine learning techniques, to rapidly visualize and iterate on multiple design experience options. The goal is to create a meaningful, interactive, data-driven/AI-assisted digital interface and physical prototype that are to be staged at an exhibition.


STUDIO BRIEF (Autumn 2018): The Augmented Museum

Today's museums are undergoing a significant process of reconceptualization, seeking new ways to curate and present their collections in both physical and digital spaces. These hybrid spaces of engagement need to be well synchronized to ensure a seamless and meaningful experience for the visitors. How does one design for a personalized experience according to the specificities of the museums' collections? We will work with a real museum or gallery and their physical and digital collections and help prototype innovative digital interfaces for exploring their collections. The course will bring together students from both IC and ENAC in a true interdisciplinary process, and consist of a non-linear process of `design charrette', `hackathon-like' and 'creative-coding' workflow. The course will contain a series of iterative design props:  `spatial-product mapping', `human-action mapping, `data-machine learning' and `prototype designing' ' as an apparatus to construct a network of understandings, and create meaningful user experiences for a final design proposal/product.


User Experience (UX) Design, Design Thinking, Creative Coding, Hackathon, Open Source, Optioneering, Iterative Prototyping

Learning Prerequisites

Required courses

Bachelor in Computer Science or equivalent

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Hackathon, Creative coding, Lectures, Design reviews, Presentations, Group projects

Expected student activities

Hackathon, Group discussion, Case studies, Design Reviews, Pin-Up, Desk Crits

Assessment methods

Grading will be based upon the quality of the projects in the preliminary stages (10% problem maps, 10% value maps, 10% data maps), intermediary reviews (20% future maps) and in the final review (50%). Final projects will be reviewed and assessed based on their conceptual strength, the coherence of their translation into prototypes, their narrative clarity and experiential power, and the persuasiveness of their communication, both orally and through the presented artifacts.


Office hours Yes
Assistants Yes



To be made available during the course

Dans les plans d'études

Semaine de référence

13-14    DIA005
15-16    DIA005
      Exercice, TP
      Projet, autre


  • Semestre d'automne
  • Session d'hiver
  • Semestre de printemps
  • Session d'été
  • Cours en français
  • Cours en anglais
  • Cours en allemand