Generative AI: A Way to Develop a Competency-Based Approach
By helping to personalize learning paths, artificial intelligence enhances the interactive aspect of learning tools, allowing the competency-based approach to be fully implemented.
Chrysta Pelissier, University of Montpellier
While the changes in education brought about by 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 lends these research questions particular relevance. Indeed, changes in educational practices have accelerated considerably in recent months, making greater use of technological tools derived in particular from generative artificial intelligence (AI).
Teachers, pupils, students, and education administrators have embraced these new ways of conveying information and sharing ideas.
Can this set of tools help develop new ways of thinking about learning, with an emphasis on a competency-based approach?
The Competency-Based Approach: An Approach Undergoing Significant Change
The competency-based approach took shape with the 2014 national framework document for degree programs leading to the award of national bachelor’s, professional bachelor’s, and master’s degrees. It was supplemented in 2018 by the decree governing the bachelor’s degree and, in 2019, by the decree governing the professional bachelor’s degree.
This approach is driving new and profound changes in universities. It is defined as an approach to teaching design that seeks to go beyond certain limitations of objective-based pedagogy.
For teachers, the changes associated with the competency-based approach relate primarily to how knowledge is conveyed and how support is provided to each student. In terms of how knowledge is conveyed, the competency-based approach represents a shift in which instructional objectives are no longer defined as content to be conveyed, but rather as practical skills that a learner must develop in order to perform their duties in a professional setting.
Faced with these new professional situations, students are led to assess their own needs in terms of knowledge, skills, and attitudes, and then to develop a process that involves selecting from their existing knowledge, conducting literature reviews, and seeking input from professionals.
Examples of how learners can use generative AI
First, in activities that encourage discovery-based learning, learners can explore and ask questions. For example, they can ask a generative AI to present scenarios specific to a profession—the one they are considering—to help them gain insight into the full range of possibilities and practice formulating hypotheses for solving each scenario.
Next, the learner can ask the AI to provide examples of careers related to the skills they have identified on their own. Note that the goal is not to impose a specific career but rather to point them toward possible career paths. It will then be up to the learner to verify the responsibilities associated with these careers and the skills required for them.
Finally, ChatGPT can help students“learn how to learn”by enabling them to plan their study sessions (“What are your priorities?”), figure out a schedule (“When are your breaks?”), consider a study method (“What did you find easy today?”), “Why?” or “Could you have done it differently?”), and receive encouragement in setting personal goals (“What do you want to understand today?”, “What was your goal for today?”, “Are you proud of yourself?”)
Examples of How Teachers Can Use Generative AI
First, educational scenarios can be developed based on original data, encouraging teachers to create escape games, quizzes, board games, or even immersive experiences tailored to a specific profession targeted by the training program.
Furthermore, generative AI applications can offer activities designed to develop skills that the learner has selected themselves, those targeted by the teacher, and also to answer questions related to a specific concept that may not have been understood in class.
By analyzing various learning materials, AI tools can help identify collective needs (within a single class) or create training materials, explanations, and feedback in different formats (text, podcasts, videos, and image collages), tailored to different learners or groups of learners.
Finally, teachers may consider offering activities designed to foster critical thinking, using various methods for creating prompts, comparing the results of multiple AI systems, and developing students’ ability to construct arguments.
This article is published as part of the Fête de la Science (which took place from October 3 to 13, 2025), of which The Conversation France is a partner. This year’s edition focuses on the theme “Intelligence(s).” Find all the events in your region on the Fetedelascience.fr website.
Chrysta Pelissier, Associate Professor of Language Sciences and Education Sciences, University of Montpellier
This article is republished from The Conversation under a Creative Commons license. Readthe original article.