Duration
15h Th, 15h Pr
Number of credits
| Master in education, professional focus | 3 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course focuses on the following topics :
- Fundamentals of generative artificial intelligence,
- The art of effective prompting,
- The roles of AI in instructional design,
- Discovery and use of various artificial intelligence tools in an educational context (in the design, teaching, learning and evaluation phases),
- Ethical and societal issues related to AI in education,
- Designing a training project incorporating AI.
- ...
Learning outcomes of the learning unit
The overall aims of the course are to ensure that students are able to :
- Master prompt engineering techniques for pedagogical purposes,
- Design an educational or training program or project by making critical and effective use of AI,
- Develop critical thinking regarding the use of AI in educational contexts,
- Use various AI tools appropriately.
Prerequisite knowledge and skills
- Know how to use a computer for office work and simple Internet browsing.
- This course is based on basic knowledge of pedagogical engineering (drawing up a lesson plan, defining objectives, establishing an assessment method, etc.)
- It is recommended that you have taken the PEDA4063 "CAPNUM" course before taking this course. The topics covered in this course will be reviewed.
Planned learning activities and teaching methods
The methodology used in this course consists, for example, of :
- Lectures given by the teacher face-to-face,
- Asynchronous online sessions (review, readings, video clips, exercises),
- Practical workshops to discover and test AI tools (conversational agents, quiz and assessment-grid generation tools, etc.),
- Gamified activities designed to develop critical thinking,
- Practical application using real-world examples.
- ...
Mode of delivery (face to face, distance learning, hybrid learning)
Blended learning
Further information:
Face-to-face for the most part, with occasional distance (asynchronous) sessions.
Course materials and recommended or required readings
Platform(s) used for course materials:
- eCampus
Further information:
On eCampus you will find the course « PEDA4070 - Artificial intelligence in education ». This is the official space for the course. You will find different types of resources throughout the course.
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions )
Further information:
Exam during the exam period - in person
Each student, individually, must design an educational or training program on a given topic (assigned at random on the day of the exam).
Students may use digital and AI tools of their choice, as well as any resources they deem useful.
Students must provide documentation of their approach and the tools used, as well as a critical reflection on their work.
It is strongly recommended that students bring their own device to the exam. However, if necessary, a device will be provided to the student.
Work placement(s)
Organisational remarks and main changes to the course
Contacts
Chargé de cours :
Jean-François Céci : jf.ceci@uliege.be
Assistants :
Lionel Biatour : lionel.biatour@uliege.be
Léa Mertens : lmertens@uliege.be