Digital Literacy I

lcomu1106  2025-2026  Louvain-la-Neuve

Digital Literacy I
3.00 credits
15.0 h + 15.0 h
Q2
Teacher(s)
Language
French
Prerequisites
At the end of this teaching unit, students will be able to:
  • Understand the fundamental concepts of computer science and digital technology
  • Use basic digital tools (such as office software and online platforms) for research, communication, and information management
  • Critically evaluate AI tools and use them responsibly and ethically in academic work and communication professions
  • Analyze a problem and identify, in simple cases, the steps necessary to solve it in the form of an algorithm (computational thinking).
General knowledge:
Knowledge:
S4. Technical skills
S9. Reflective approaches (issues)
Skills:
SF1. Identify issues
SF11. Critique/Deconstruct
SF12. Mastering tools
Attitudes:
SE1. Active listening
SE2. Participation
SE4. Planning
SE5. Meeting deadlines
SE7. Critical thinking
Specific knowledge:
SP3. Software proficiency
SP7. Statistics
Main themes
This course is the first of three courses designed to equip students with the skills they need to navigate effectively, knowledgeably, and critically in an ever-changing digital environment. In the specific case of this first course, LCOMU1106, the following topics will be covered:
  • Basic computer literacy: computers, networks, data (text, images, sound, video)
  • Office automation and digital tools for research, communication, and information management
    • Word processing, spreadsheets, creation of visual presentations (such as Word, Excel, PowerPoint)
    • Bibliographic reference management tools (such as Zotero)
    • Relevant, ethical, and critical use of artificial intelligence tools for office automation
    • Algorithms and computational thinking
Content
UAA 1 - Basic computer literacy
  • Computers and how they work
  • Computer networks: architecture and protocols
  • Digital data
UAA 2 - Office automation and digital tools for research, communication, and information management
  • Word processing
  • Spreadsheets (see UAA3)
  • Creating visual presentations
  • Managing bibliographic references
UAA 3 - Algorithms and computational thinking
  • Breaking down a problem into sub-problems
  • Basics of programming: loops, conditions, and variables
Teaching methods
Interactive and progressive teaching approach, comprising:
  • Lectures: Introduction of key concepts accompanied by practical demonstrations of relevant tools.
  • Formative assessment: Use of quizzes and hands-on exercises to monitor students’ understanding and their ability to apply concepts or technics throughout the course.
  • Supervised summative exercises: Application of acquired knowledge to one or more concrete case studies, under monitored conditions.
Evaluation methods
  • Continuous assessment: Three supervised integrative assignments (with the support of teaching assistants).
  • Active participation: Bonus of up to 10% based on engagement during class sessions.
  • No final exam in the first exam session.
Second exam session
  • Written exam: Comprehensive assessment covering the entire course content, including the self-study modules on Moodle.
  • The participation bonus will not be applied in the second session.
Other information
In this course, the use of AI tools is regulated in accordance with the guidelines outlined in the AI Smart Teaching note: https://oer.uclouvain.be/jspui/handle/20.500.12279/1007.
Students are expected to comply with the following principles:
  • Transparency: If you use an AI tool to assist with writing, research, or structuring your ideas, you must explicitly acknowledge it in your work. This includes tasks such as language correction, translation, outlining, or text summarization.
  • Authenticity: All submitted work must reflect your own understanding and skills. AI must not substitute for, or obscure, your intellectual and critical engagement.
  • Responsibility: You remain fully accountable for the content you submit, even when AI tools have been used. Any undeclared or inappropriate use may be considered academic misconduct and sanctioned under the Study and Examination Regulations (notably Chapter 4, Section 7 of the RGEE).
  • Retention: Records of interactions with AI tools used in the production of assignments must be preserved and made available for verification until final results are released.
In addition, in line with principles of energy efficiency and ecological responsibility, the use of generative AI should be limited to what is strictly necessary for the task at hand. Its use is strictly prohibited whenever assignment instructions explicitly forbid it, or implicitly do so by requiring a personal production, unless prior authorization has been granted.
English-Friendly Course
  • Questions: Students may ask questions in English.
  • Dictionary: Students are permitted to use a dictionary (either a monolingual French dictionary or a bilingual French–mother tongue dictionary, as specified by the instructor), including for assignments.
  • Assignments: While course materials are primarily in French, assignments for continuous assessment may be submitted in either French or English.
Online resources
All course materials and updates are available on the Moodle course space
Faculty or entity


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

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Bachelor in Information and Communication