ID:
SCV0848
Durata (ore):
48
CFU:
6
SSD:
INFORMATICA
Anno:
2024
Dati Generali
Periodo di attività
Primo Semestre (23/09/2024 - 20/12/2024)
Syllabus
Obiettivi Formativi
The course provides an overview of the main theories, concepts, principles, techniques, heuristics and tools for the design, development and evaluation of interactive data graphics.
The student will acquire the knowledge and skills related to:
Objective 1 (O1) – knowledge of theory and principles:
1) Theories of perception, cognitive biases, notions of semiotics and pragmatics;
2) Data types and physical signals (pre-attentive selection, color theory, gestalt theory, and the like);
Objective 2 (O2) – knowledge of basic concepts and models
3) The grammar of data graphics and its application to encoding and decoding of visual information;
4) Classifications and taxonomies of data graphics;
5) Main design principles;
6) Models and heuristics for a proper interaction design of visual interfaces;
Objective 3 (O3) – Practice, applications and evaluation of concepts and models:
7) Tools and resources for the advanced design of data graphics, static and interactive infographics, and dashboards (Python libraries and Tableau);
8) Main techniques for choosing and applying the best qualitative and quantitative evaluation test to data graphics and interactive dashboards;
9) Notions of visual information literacy and statistical techniques for its evaluation;
Objective 4 (O4) – Soft skills
10) Communication skills related to the acquisition and application of the visual language of data;
11) Evaluation skills related to the quality assessment of visual artifacts and tools.
The student will acquire the knowledge and skills related to:
Objective 1 (O1) – knowledge of theory and principles:
1) Theories of perception, cognitive biases, notions of semiotics and pragmatics;
2) Data types and physical signals (pre-attentive selection, color theory, gestalt theory, and the like);
Objective 2 (O2) – knowledge of basic concepts and models
3) The grammar of data graphics and its application to encoding and decoding of visual information;
4) Classifications and taxonomies of data graphics;
5) Main design principles;
6) Models and heuristics for a proper interaction design of visual interfaces;
Objective 3 (O3) – Practice, applications and evaluation of concepts and models:
7) Tools and resources for the advanced design of data graphics, static and interactive infographics, and dashboards (Python libraries and Tableau);
8) Main techniques for choosing and applying the best qualitative and quantitative evaluation test to data graphics and interactive dashboards;
9) Notions of visual information literacy and statistical techniques for its evaluation;
Objective 4 (O4) – Soft skills
10) Communication skills related to the acquisition and application of the visual language of data;
11) Evaluation skills related to the quality assessment of visual artifacts and tools.
Prerequisiti
Students should have acquired a background knowledge on data preparation and statistics.
Programming skills in Python may improve the chance to acquire a deeper knowledge of tools usage.
No other pre-requisites are required.
Programming skills in Python may improve the chance to acquire a deeper knowledge of tools usage.
No other pre-requisites are required.
Metodi didattici
The course consists of lessons (48 hours).
Lessons deal with the overall set of topics listed above using conceptual, formal descriptions and with the support of demo, case studies, on line resources, and small tasks given to students as exercise and further investigation. Open discussions with students during lessons are encouraged.
Lessons deal with the overall set of topics listed above using conceptual, formal descriptions and with the support of demo, case studies, on line resources, and small tasks given to students as exercise and further investigation. Open discussions with students during lessons are encouraged.
Verifica Apprendimento
The exam will consist of a theory part (half of the final vote) and a practical part (half of the final vote). In particular, the two parts will consist of:
- an online quiz with yes/no, multi-choice and open questions, assessing the student’s knowledge of the topic;
- a small team project, where students will apply the skills and knowledge of the course to preprocess, implement and / or evaluate an infographics and/ or a dashboard.
The final exam will be passed with a minimum grade of 18/30.
- an online quiz with yes/no, multi-choice and open questions, assessing the student’s knowledge of the topic;
- a small team project, where students will apply the skills and knowledge of the course to preprocess, implement and / or evaluate an infographics and/ or a dashboard.
The final exam will be passed with a minimum grade of 18/30.
Contenuti
The following topics will be touched and discussed into depth:
(O1 – 12 h)
1) Theories of perception, cognitive biases, semiotics and pragmatics. Basic notions of:
a. The Visual system (2h);
b. Cognitive models of attention, perception, action for decision-making (2h);
c. Cognitive biases (2h);
d. Principles of semiotics (2h)
2) Data types and physical signals (pre-attentive selection, color theory, gestalt theory, and the like). Basic notions of:
- Color theory (1h)
- Gestalt theory (shape) (1h)
- Information, Communication and Visual language (2h);
(O2 – 24h)
3) The grammar of data graphics and its application to encoding and decoding of visual information:
a. Importance of the context (4h)
a. Choosing an effective visual (4h)
b. Clutter is your enemy (4h)
c. Focus your audience's attention (4h)
d. Dissecting model visuals (4h)
e. Lessons in storytelling (4h)
(O3 – O4 – 23h)
7) Tools and resources for the advanced design of single charts, static and interactive infographics, and dashboards. Overview, demo, practical examples and use of the following tools (10h):
a. Python libraries (Matplotplib and others) (4h);
a. Tableau (4h);
8) Notions of techniquest to allow interaction with data (4h).
(O1 – 12 h)
1) Theories of perception, cognitive biases, semiotics and pragmatics. Basic notions of:
a. The Visual system (2h);
b. Cognitive models of attention, perception, action for decision-making (2h);
c. Cognitive biases (2h);
d. Principles of semiotics (2h)
2) Data types and physical signals (pre-attentive selection, color theory, gestalt theory, and the like). Basic notions of:
- Color theory (1h)
- Gestalt theory (shape) (1h)
- Information, Communication and Visual language (2h);
(O2 – 24h)
3) The grammar of data graphics and its application to encoding and decoding of visual information:
a. Importance of the context (4h)
a. Choosing an effective visual (4h)
b. Clutter is your enemy (4h)
c. Focus your audience's attention (4h)
d. Dissecting model visuals (4h)
e. Lessons in storytelling (4h)
(O3 – O4 – 23h)
7) Tools and resources for the advanced design of single charts, static and interactive infographics, and dashboards. Overview, demo, practical examples and use of the following tools (10h):
a. Python libraries (Matplotplib and others) (4h);
a. Tableau (4h);
8) Notions of techniquest to allow interaction with data (4h).
Lingua Insegnamento
INGLESE
Altre informazioni
The professor receives by appointment, upon request via email at andrea.biancini@uninsubria.it. The professor responds only to emails that are signed and originate from the domain studenti.uninsubria.it.
Corsi
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INFORMATICA
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