The course aims to provide the basic computer knowledge necessary to enable an informed use of network resources and common productivity software tools that could be useful in the specific application domain of the course of study.

1. Introduction
The theoretical and technological pillars of automatic information processing

2. Digital representations
What is information
What does "digital" mean
Binary encodings and file sizes

3. Computational thinking
Programmable objects and programming languages
The concept of algorithm
The practice of coding

4. Hardware
Hardware architecture of a computer
Processor Memory hierarchy (cache, RAM, Virtual memory)
Peripherals

5. Software
Software architecture: Firmware, OS, applications
Life cycle of a program
The operating system and file management

6. Communication
Communication channels
Computer networks
Internet: historical notes, founding principles, protocol stacks, applications

7. Network, Web and cloud services
Client-server model
The World Wide Web Web
Cloud computing

8. Online responsibility, privacy and security
Social networks
Privacy, security and responsibility
Credential management

9. Cloud productivity
Overview of key productivity tools
Online collaboration, permission management, common problems

10. Spreadsheets
Structure and functionality of a spreadsheet

11. Application Examples
Representation and processing of the results of a measurement experiment

None

Knowledge and understanding: the meaning of terms "information" and "digital", fundamental principles of computer science, Internet, web and cloud 

Applied knowledge and understanding: ways of representing and managing digital information, in particular in relation to the transmission of data on the Internet and the use of Web and cloud technologies, potential of productivity software tools and online collaboration tools

Making judgements: principle of responsibility online, good usage practices

Communication skills: conscious use of IT tools and online resources, proper use of specific IT terms

Learning skills: computational thinking skills as a transversal soft skill, application of basic principle of computer programming to understand the algorithmic and computational aspects of everyday tasks and processes

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Teaching

Lectures with practical examples

Attendance

Attendance of more than 2/3 of lectures

Course books

Lecture note provided by the instructor

Assessment

Attendance of 2/3 of lectures and online test

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

Blended learning

Course books

Learning materials provided by the instructor

Assessment

Final test plus oral examination

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.