AIMS AND CONTENT

LEARNING OUTCOMES

The evolution of human-machine interfaces is presented, from operating systems to mobile and immersive platforms. The main aim is to acquire the knowledge and main technical skills for the design of responsive, multimedia, mobile-first and immersive human-machine interfaces

AIMS AND LEARNING OUTCOMES

Aims:

• Understand the principles of Digital Communication, Human-Machine Interaction, and the interfaces of major Operating Systems. Understand the functioning principles of the Internet and Computer Networks.
• Understand the functioning principles of search engines, SEO/SEM, and related tools.
• Know the main formats and software tools used in digital media for designing, creating, and distributing digital content (text, images, audio, video, computer graphics).
• Consciously understand the functioning principles of major machine learning models (Machine Learning and Deep Learning) and the impact of Generative Artificial Intelligence in current media.

Learning Outcomes:

• Be able to design and create simple applications and digital content, particularly for web, CMS, social networks, digital audio-video broadcasting, podcasts, web-radio, and web-TV.

TEACHING METHODS

Unit 1 of Digital Communication has mandatory attendance. It will be delivered through lectures and technical-practical laboratory activities in person, using Active Learning and Flipped Classroom methodologies. Some extra-curricular thematic seminars complement the main teaching methods.

The module is also associated with some tutorial MOOCs (both in English and Italian).

SYLLABUS/CONTENT

PART A - THEORY

1. Digital Communication and ICT Technologies

•  Communication and Technologies of the 21st century: digital convergence, Internet, Information and Knowledge Management, Trends.
•  The main models and theories underlying Digital Communication.
•  Designing software applications and computational thinking: methods, algorithms, tools, data, formats, media.

2. Human-Machine Interaction and Operating System Architectures

• Theoretical models of interaction and management of human-machine interfaces, with particular reference to user interfaces of computers and smart devices (shell, windowed, multimodal, multitouch, and natural interfaces).
• The architectures and components of operating systems, with particular reference to the comparative description of Microsoft (especially Windows 11), Apple (MacOs), Linux (Ubuntu), and mobile (Android, iOS) operating systems.

3. Internet, TCP/IP, Search Engines, SEO/SEM

• The functioning principles, structure, and organization of computer networks, with particular reference to the ISO/OSI model and TCP/IP protocols. The http protocol, the Data Web, and the Internet of Things.
• Search engines, queries, and search engine positioning, SEO/SEM principles.

4. Digital Communication and Artificial Intelligence

• History of Artificial Intelligence and current impact on Digital Communication.
• The functioning principles of major deep learning models (Machine Learning, Deep Learning, Large Language Models, Generative AI).
• Generative AI: introduction to multimodal Prompt Programming, methodologies for designing and co-generating multimodal content with GPT and diffusion models.
• Prompt programming tools for text, digital images, audio, and video.

5. Designing and producing podcasts and multimedia content

• Designing and producing podcast content.
• Organizing and producing content for webradio and webtv.

PART B – LABORATORY AND PROJECT ACTIVITIES

1. Digital Technologies for the Web

• Designing and creating web layouts: HTML and CSS languages; the box model and DOM.
• Programming and data management for the web: Javascript, PHP, and SQL languages for data management.
• Realization of Responsive Web Design based sites for HTML 5.0.

2. Generative AI Laboratory

• GenAI technologies and tools for generating audio-video content.
• Designing and producing podcast content.
• Managing and organizing audio-video livestream for webradio and webtv.

RECOMMENDED READING/BIBLIOGRAPHY

Recommended reference texts (in Italian, original version in English):

• B. W. Kernighan -  Informatica - Orientarsi nel labirinto digitale, Egea Italia, 2019
• E. Saravia – Guida al Prompt Engineering, 2024, DAIR.AI https://www.promptingguide.ai/it.

Recommended handouts and video courses (in Italian):

• G. Vercelli - G. Olivieri, Orientarsi nel mondo digitale, dispensa creative common disponibile su Aulaweb, edizione 2020
• G. Vercelli - G. Olivieri, Storia dei Sistemi Operativi, dispensa creative common disponibile su Aulaweb, edizione 2019
• G.Vercelli - E. Bellanti - Fondamenti di Informatica - videocorso EduOpen  - disponibile su https://learn.eduopen.org/
• A.Merlo - I.Torre - M. Ribaudo -  Internet  e il mondo delle reti- videocorso EduOpen - disponibile su https://learn.eduopen.org/
• M.Cerioli - M.Reggio -  Scrivere e far di conto nell'era digitale​- videocorso EduOpen - disponibile su https://learn.eduopen.org/
• AA.VV., W3SCHOOLS Online Web Tutorials, risorse tutoriali sulle tecnologie web, disponibile su http://w3schools.com

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

The timetable for this course can be found at: Portale EasyAcademy

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

In order to take the exam, 2 mutually exclusive methods are possible:

MODE A) (intermediate tests during the course, for "attending" students)

During the course, continuous evaluation is foreseen through in-person activities carried out in the classroom, in the laboratory and remotely on the platforms made available by the University, with the obtaining of the relevant scores which will allow access to the final individual assessment (scheduled at the end of the course, on a DATE NOT NECESSARILY COINCIDENT WITH THE OFFICIAL APPEAL DATES).

MODE B) (written and oral exam, for "non-attending" students)

Written tests (1 online test on knowledge and 1 practical test on skills), followed by oral exam to be carried out EXCLUSIVELY ON THE OFFICIAL APPEAL DATES. Registration is mandatory electronically via the online exam booking service established by the University.

ASSESSMENT METHODS

The skills assessment method will be diversified based on frequency.

• For those who attend the laboratory activities (both in person and remotely) during the course ("attending" students), a continuous evaluation will be adopted based on the submissions made on Aulaweb and the passing of the self-assessment tests made available online, at in order to allow the timely achievement of the training objectives and key skills to be verified in the final individual test.
• For those who do not attend regularly ("non-attending" students), a mixed evaluation will be adopted, in which they will be asked to pass the online self-assessment tests, and then 2 individual written tests will be administered (an online test and a technical test). practice) followed by an oral exam, in order to verify both the level of theoretical and methodological preparation and the objective practical skills and competences.

FURTHER INFORMATION

For students with disabilities or specific learning disorders (SLD):

Students with disabilities or with a specific learning disorder (SLD) are reminded that, in order to request exam accommodations, they must first upload their certification to the University website at servizionline.unige.it under the "Students" section. The documentation will be verified by the University’s Office for the Inclusion of Students with Disabilities and SLDs (https://rubrica.unige.it/strutture/struttura/100111).

After this step, and well in advance (at least 10 days) before the exam date, students must send an email to the instructor responsible for the exam. The email must also be cc’d to both the School’s Inclusion Coordinator for students with disabilities and SLDs (Prof. Laura Traverso, laura.traverso@unige.it) and the above-mentioned office, using one of the following addresses:

• disabili@unige.it

• dsa@unige.it

• inclusione.studenti@info.unige.it

The email must include the following information:

• the name of the course

• the date of the exam

• the student’s full name and student ID number

• the requested compensatory tools and dispensatory measures deemed necessary.

The coordinator (Prof. Laura Traverso) will confirm to the instructor that the student is entitled to request accommodations and that these should be discussed and agreed upon with the instructor. The instructor will then respond indicating whether the requested accommodations can be applied.

Requests must be submitted at least 10 days before the exam date to allow the instructor sufficient time to review them. In particular, if the student intends to use concept maps during the exam (which must be much more concise than those used for studying), failing to meet the deadline may result in insufficient time to make any modifications that the instructor might request.

For further information on how to request services and accommodations, please consult the document:
Guidelines for requesting services, compensatory tools and/or dispensatory measures, and specific aids.