lcomu2811  2020-2021  Louvain-la-Neuve

Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h
Q2
Teacher(s)
Kieffer Suzanne;
Language
French
Main themes
·         Visual perception
·         Representation (encoding of values, of relations)
·         Presentation (visualization techniques) and interaction
·         Design principles (Gestalt, Bertin, color theory)
·         Dashboards and visual analytics
Aims

At the end of this learning unit, the student is able to :

1. Describe data visualizations in terms of data type, data representation, presentation and interaction technique, and user task ;
 
2. Explain the different stages involved in the development of interactive visualizations by illustrating each step through its typical results (e.g. deliverables) ;
 
3. Apply Information Visualization principles and techniques to design and develop an interactive visualization of a large data set ;
 
4. Evaluate a visualization using criteria and propose improvements.
 
Content
Visual perception
Processing, representation and presentation of data
Interaction with data
Design principles
Trends: dashboards and visual analytics
Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The instructional approach is blended teaching, which alternates remote online teaching via Microsoft Teams and face-to-face classroom teaching. The distribution between distance and face-to-face is adapted according to the evolution of the health situation. For example, it is possible to switch from one in two face-to-face sessions (“yellow scenario”) to one in three face-to-face sessions (“orange scenario”), and vice versa. In addition, some sessions are replaced by independent work activities carried out individually (e.g. following tutorials or encoding a sheet in a database) or in groups (e.g. creating an interactive data visualization).
The teaching methods are flipped classroom and project-based teaching:
  • Flipped classroom: students study the material at home and then meet their teacher and peers in a classroom to ask questions and get additional help or to work with their peers;
  • Project-based teaching: students develop a project by combining online learning and face-to-face meetings.
Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Formative assessment (there is therefore no certification exam at the end of the term) according to three modes: exercises and knowledge tests, individual assignments and group assignments. Each mode accounts for 33.33% of the final grade. The validation of the credits associated with this course requires the successful completion in each mode.
Second session: personalized individual assignment to be delivered on the first day of the session.
Other information
All relevant information regarding these modalities and the progress of the activities (calendar, detailed instructions, evaluation criteria, etc.) are presented during the first course and are available on Moodle.
Some resources (e.g. bibliographic resources, slides, explanatory videos) are in English.
Online resources
Moodle (asynchronous): course slides, bibliographic resources, calendar, models and rubrics, H5P exercises, tests, assignments, workshops with peer assessment, group choice, Q&A forum
Microsoft Teams (live): calendar, meetings, documents, discussion, lecture notes
Web links: how-to videos, websites, online software
Tableau software (https://www.tableau.com/) : online tutorials, academic license with UCLouvain email address.
Bibliography
Bateman, S., Mandryk, R. L., Gutwin, C., Genest, A., McDine, D., & Brooks, C. (2010, April). Useful junk?: the effects of visual embellishment on comprehension and memorability of charts. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2573-2582). ACM.
Bertin, J. (1983). Semiology of graphics; diagrams networks maps (No. 04; QA90, B7.).
Cairo, A. (2015). Graphics lies, misleading visuals. In New Challenges for Data Design (pp. 103-116). Springer, London.
Heer, J., Bostock, M., & Ogievetsky, V. (2010). A tour through the visualization zoo. Commun. Acm, 53(6), 59-67.
Fox, W. Statistiques sociales. Traduction et adaptation de la troisième édition américaine par Louis Imbeau, De Boeck, 1999.
Spence, R. Information Visualization: Design for Interaction. 2007.
Tufte, E. The visual display of quantitative information, 2nd edition. Graphics Press. 2001.
Ware, C. Information Visualization, 3rd Edition, Perception for Design. Morgan Kaufmann. 2012.
Faculty or entity
COMU


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [60] in Information and Communication

Master [120] in Information and Communication Science and Technology

Master [120] in Communication