Generative AI, a means of developing the competency-based approach
By helping to personalize learning paths, artificial intelligence enriches the interactive dimension of learning tools, allowing the skills-based approach to be fully deployed.
Chrysta Pelissier, University of Montpellier
While the changes that have begun in education with and through digital technology have been an interesting phenomenon to study since their emergence, the release of ChatGPT 5 (GPT-5) on August 7, 2025, by OpenAI gives these research questions particular relevance. Developments in educational practices have accelerated considerably in recent months, leaving more room for technological tools, particularly those based on generative artificial intelligence (AI).
Teachers, pupils, students, and training managers have embraced these new ways of transmitting information and sharing ideas.
Can this range of tools help develop new ways of approaching learning, with a focus ona skills-based approach?
The competency-based approach, a rapidly changing process
The skills-based approach took shape with the national framework document for training programs leading to national bachelor's, professional bachelor's, and master's degrees in 2014. It was supplemented in 2018 by the decree on bachelor's degrees and in 2019 by the decree on professional bachelor's degrees.
This approach is driving new and profound changes in universities. It is defined as a way of designing teaching that attempts to overcome certain limitations of objective-based pedagogy.
For teachers, the changes associated with the competency-based approach are particularly evident in the methods used to impart knowledge and provide support to individual students. In terms of teaching methods, the competency-based approach appears to be a movement in which teaching objectives are no longer defined as content to be imparted, but rather as skills that learners must develop in order to be able to perform their tasks in a professional situation.
Faced with these new professional situations, students are encouraged to identify their own needs in terms of knowledge, skills, and attitudes, and then to develop a process for selecting personal knowledge (already acquired), conducting documentary research, and consulting with professionals.
Examples of uses of generative AI for learners
First, in activities that stimulate learning through discovery, learners can explore and ask questions. For example, they can ask a generative AI to suggest situations specific to a profession they are considering, allowing them to glimpse their diversity, but also to practice formulating hypotheses for resolving each of them.
Next, learners can ask the AI to give them examples of jobs related to their own skills, which they will have identified themselves. It is important to note that the aim is not to impose a particular job, but rather to point them toward possible careers. It will then be up to them to check the tasks associated with these jobs and the skills required for them.
Finally, ChatGPT can help them "learn how to learn" by enabling them to plan their revision ("What are your priorities?"), identify how to allocate their time ("When are your breaks?"), consider a working method ("What did you find easy today?", "Why?" or "Could you have done things differently?"), and receive encouragement in setting personal goals ("What do you want to understand today?", "What was your goal for the day?", "Are you proud of yourself?").
Examples of uses of generative AI for teachers
First, educational scenarios can be developed based on original data, leading teachers to offer escape games, quizzes, board games, or even immersive contexts specific to a profession targeted by the training program.
Next, generative AI practices can offer activities aimed at developing skills that the learner has selected themselves, those targeted by the teacher, but also answering questions related to a particular concept that may not have been understood in class.
By analyzing multiple media, AI tools can help identify collective needs (within the same class) or create training materials, explanations, and feedback in different formats (text, podcasts, videos, and image montages) tailored to different learners or groups of learners.
Finally, teachers may consider offering activities that focus on critical thinking, using different prompt creation methodologies and comparing the results of several AIs while developing argumentation skills.
This article is published as part of the Fête de la science (Science Festival), which took place from October 3 to 13, 2025, and of which The Conversation France is a partner. This year's theme is "Intelligence(s)." Find all the events in your region on the Fetedelascience.fr website.
Chrysta Pelissier, Senior Lecturer in Language Sciences and Education Sciences, University of Montpellier
This article is republished from The Conversation under a Creative Commons license. Readthe original article.