2023-2024 / PEDA0072-1

Digital teaching-learning and computational thinking


15h Th, 10h Pr

Number of credits

 Master in education (120 ECTS)3 crédits 


Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Please note that this elective is only offered every other year, in even-numbered years (2020-2021, 2022-2023,...).

The course includes the design and analysis of activities aiming at the development of computational thinking as well as their field experimentation.

  • Definitions and characteristics of Computational Thinking
  • Competencies framework
  • Concepts/notions (algorithm, variable, loop, sequence of actions, Artificial Intelligence...)
  • Pugged activities (e.g. use of robots, programming languages) and unplugged ones (without the use of technological tools)
  • Pedagogical scenario respecting the triple concordance between targeted competencies, learning activities and evaluation
  • Problem solving approaches
  • Reflexivity
  • ...

Learning outcomes of the learning unit

The main course's objectives are (for the students):

  • learning how to build, implement and analyze teaching-learning devices for the development of Computational Thinking (CT) among students from kindergarten to high school.
  • reflecting on the training of teachers/trainers in the field of CT.
More specifically, learners will be able to :

  • define "Computational Thinking"
  • appropriate a competency framework (for young people of different age groups)
  • acquire (part of) the competencies framework
  • understand complex problems, break them down into sub-problems, propose solutions that can be partially or fully automated
  • link a (series of) learning activities to one or more competencies
  • analyze various existing activities, particularly in terms of the triple alignment between target competencies, learning activities and evaluation
  • design a pedagogical scenario for the development of CT
  • implement their scenario in a given context
  • make links between these activities and teachers/trainers' training
  • take a reflexive look at their learning process and their productions

Prerequisite knowledge and skills

Planned learning activities and teaching methods

  • Collect learner's conceptions/representations of Computational Thinking (CT)
  • Brief presentation of the competency framework "PIAF" (origin, comparison with other competencies framework)
  • Pluged and unplugged activities in sub-groups (+ note taking)
  • Presentation of the pedagogical scenario framework
  • In sub-groups, completing part of the canvas based on the experience of a workshop 
  • Group debriefing
  • Intervention of external expert(s)
  • Analysis of existing activities or scenarios (observation grids)
  • Online resources exploration
  • Testing of different hardware (e.g. different types of robots or languages)
  • Co-creation in duo, mainly conducted and tutored at a distance, of a pedagogical scenario (personal choice of the learners validated by the teacher) based on a provided framework
  • Field experimentation (of part) of the scenario
  • Filling an individual reflective roadbook throughout the process

Mode of delivery (face to face, distance learning, hybrid learning)

Blended learning

Additional information:

Two sessions (9.00 to 17.00) will take place in "face-to-face" (wednesday 22/2/23 and tuesday 23/2/23). The following activities will be tutored online. 

The student have to participate to the two days in "face-to-face" to validate the course. 

Recommended or required readings

All the documents will be put online progressively on eCampus. 

Exam(s) in session

Any session

- In-person

oral exam

Written work / report

Additional information:

The evaluation is based on :

1) the design of a pedagogical scenario aiming at developing computational and algorithmic thinking among young people or in (future) supervisors

2) keeping a reflexive roadbook throughout the learning activities, including a brief report on the partial or total experimentation of the scenario including possible outlooks

3) the oral presentation of the implementation of the pedagogical scenario.

Validation requests the submission of the three parts to vaidate the exam. 

Work placement(s)

Organisational remarks and main changes to the course


Profesor :
Brigitte Denis, b.denis@uliege.be
Teacher's assistant : 
Sarah Higuet, sarah.higuet@uliege.be

Association of one or more MOOCs