Introduction au data journalisme

Teacher(s)

Descampe Antonin; Kieffer Suzanne;

Language

French

Content

• Context: data for journalism
• Data processing: acquisition, cleaning and verification, analysis and visualization
• Data storytelling in journalistic production

Teaching methods

The pedagogical approach is blended teaching, which alternates face-to-face classroom teaching with online distance learning via Microsoft Teams. Teaching methods include face-to-face teaching, flipped classroom and project-based learning:

• Flipped classroom: students study or complete an assignment at home and then meet with teachers and peers in a classroom to ask questions, get extra help or work in groups;
• Project-based learning: students develop a project by combining online learning (e.g. watching tutorials) and face-to-face meetings.

Evaluation methods

Continuous assessment without examination in January in two modes: individual and/or group assignments accounting for 70% of the final grade, and knowledge tests accounting for 30% of the grade. In September, individual custom assignment due on the first day of the session.
Use of AI tools
The use of artificial intelligence during the assessments of this course is governed by the rules mentioned in the faculty note on this subject and available on the faculty intranet site in the information for students.

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, Q&A forum
Microsoft Teams (live): calendar, meetings, documents, discussion, lecture notes
Web links: how-to videos, websites, online software

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. (1999). Traduction et adaptation de la troisième édition américaine par Louis Imbeau, De Boeck.
Spence, R. (2007). Information Visualization: Design for Interaction.
Tufte, E. (2001). The visual display of quantitative information, 2nd edition. Graphics Press.
Ware, C. (2012). Information Visualization, 3rd Edition, Perception for Design. Morgan Kaufmann.

Faculty or entity

> COMU