Publish at May 13 2026 Updated May 13 2026
Autonomy is now a given in vocational training discourse. It permeates skills repositories, structures pedagogical expectations and is often an implicit criterion for assessing learners and practicing professionals alike.
To be autonomous is to be able to act without constant supervision, to make appropriate decisions, to organize oneself effectively and to be accountable for one's actions. In the healthcare sector in particular, this autonomy is elevated to the rank of a cardinal quality, inseparable from the responsibility and safety of care. It thus appears as a marker of professional maturity, a threshold to be reached, if not a standard to be embodied.
And yet, the closer we get to it, the more the notion slips away. For although autonomy is omnipresent, it is rarely precisely defined. Exactly what autonomy are we talking about?
This plurality of meanings, rarely spelled out, contributes to a conceptual vagueness that weakens its operational scope.
This vagueness is not without consequences. It authorizes a form of implicit normativity. Autonomy thus becomes less an objectifiable skill than a diffuse expectation, a horizon towards which to strive without its contours being stabilized. It distinguishes, without always saying so, between professionals who are deemed "competent" and those who are not, and between trainees who are "ready" and those who need more supervision. In this sense, autonomy functions as a means of regulating behavior, even as a sorting tool, rather than as a clearly identified, taught and assessed skill.
This ambiguity is reflected in the training systems themselves. How can autonomy be trained if it is neither precisely defined, nor broken down into observable components? How can we guide learners towards an objective whose criteria remain implicit?
The injunction to autonomy can then take the form of a pedagogical paradox: the aim is to be autonomous... without the conditions of possibility of this autonomy being explicitly constructed. In some cases, this injunction may even mask implicit institutional expectations, or even strong organizational constraints, placing the learner in a position of permanent adjustment.
Added to this complexity today is the profound transformation of learning and working environments, marked by the rise of digital technologies and, more recently, generative artificial intelligence. These tools promise to increase people's capacity for action: easier access to information, decision support, structuring of reasoning, automation of certain tasks. In appearance, they contribute to a form of "enhanced autonomy".
But at the same time, they introduce new, more diffuse and sometimes invisible forms of dependence, where cognitive delegation can gradually replace the effort to understand. So, does being autonomous still mean acting alone, or knowing how to effectively mobilize external human and technological resources?
The question of autonomy cannot be dissociated from the concrete conditions in which it is exercised. It is neither a purely individual disposition, nor an intrinsic quality of the subject, but a relationship between an individual, an environment and tools. In this sense, to speak of autonomy as a stable, transferable skill seems reductive. Rather, it should be seen as a dynamic, evolving capacity, dependent on contexts and available resources.
This is the starting point for the discussion in this article.
Beyond a simple conceptual clarification, the stakes are high. If autonomy remains a vague injunction, it runs the risk of producing paradoxical effects: empowering without equipping, evaluating without clarifying, and even weakening individuals by sending them back to a requirement they cannot fully grasp.
Conversely, by placing it in the context of the concrete conditions of its emergence, it becomes possible to transform it into a genuine training object, and no longer into a simple, supposedly shared, self-evident fact.
Autonomy occupies a singular place in skills frameworks, particularly in professional training courses and, emblematically, in the healthcare professions. It appears both as a goal and as a transversal indicator of professionalism.
Rarely isolated as a specific skill, it permeates all expectations: the ability to act appropriately, to adapt to complex situations, to make informed decisions, to assume responsibility. Autonomy is thus called upon at every level of professional development, from the earliest stages of learning to the most advanced.
This omnipresence is not accidental. It reflects changing expectations of professionals, who are now called upon to intervene in uncertain environments, marked by the complexity of situations, the variability of contexts and the need for rapid arbitration.
In this context, the simple application of protocols is no longer sufficient: professionals are expected to demonstrate discernment, initiative and adaptability. Autonomy thus becomes the sign of a built-in competence, capable of manifesting itself beyond explicit prescriptions.
However, this centrality is accompanied by a form of dilution. Because it is everywhere, autonomy is rarely circumscribed: it is at once what is targeted, what is observed and what is expected, without these three dimensions being clearly distinguished. Paradoxically, this ubiquity contributes to weakening its operative scope.
One of the most striking features of the notion of autonomy is the absence of a consensual, stabilized definition. Depending on the context, the discourse and the players involved, it refers to heterogeneous realities, sometimes complementary, sometimes contradictory.
This plurality of meanings is not in itself problematic. It reflects the richness of a notion that touches on multiple dimensions of professional activity. What is more problematic, on the other hand, is the absence of any explicit reference to these different dimensions in reference frameworks and training systems. In the absence of clarification, autonomy tends to be taken for granted, and assumed to be understood by all, even though it covers distinct realities.
This lack of clarity has concrete effects. It makes it difficult to construct targeted learning situations, since it is not clear what needs to be developed. It also complicates assessment, in the absence of explicit criteria for objectifying expectations. Finally, it opens the way to varying interpretations by trainers, tutors or institutions, potentially generating inequalities of treatment and misunderstandings among learners.
Thus, far from being a stabilized skill, autonomy appears to be a polymorphous notion, whose contours fluctuate according to context and usage. This conceptual instability directly questions its relevance as an object of teaching and assessment.
Beyond its definitional vagueness, autonomy stands out for its strong normative dimension. It doesn't just describe an ability; it prescribes an expected behavior. In many professional contexts, being autonomous is not just another skill, but an implicit and sometimes non-negotiable requirement. It becomes a criterion of judgment, often mobilized to qualify the progress of a learner or the quality of a professional.
This normative dimension is particularly marked in assessment situations. The learner is judged as "autonomous" or "not yet autonomous", without the criteria for this assessment always being made explicit. In this case, autonomy functions as a global, synthetic indicator, condensing a series of observations without necessarily making the basis explicit. It makes it possible to formulate a rapid judgment, but at the cost of a certain opacity.
This implicit nature gives autonomy a regulatory function. It helps to guide expected behavior, to indicate what is valued in a given professional environment. It contributes to the construction of a norm, sometimes internalized by the learners themselves, who seek to conform to what they perceive as the environment's expectations. From this perspective, autonomy is not just a skill to be acquired; it becomes a professional ideal, even a marker of belonging.
However, this normativity is not without risk. In the absence of explicit criteria, it can lead to subjective assessments, dependent on the individual representations of trainers or tutors. It can also generate paradoxical injunctions, particularly when autonomy is expected in highly constrained environments, where real room for manoeuvre is limited. The learner may then find himself summoned to be autonomous without having the necessary conditions to do so effectively.
Autonomy thus appears less as an objectifiable skill than as a social and institutional construct, invested with multiple meanings and carrying implicit expectations. This observation prompts us to question the conditions under which autonomy can be effectively developed in training programs, which in turn leads us to examine more precisely the way in which autonomy is, or is not, taught.
[Aporia: unsolvable problem as posed] - Training for autonomy presupposes, in the first instance, that it can be identified as an object of learning in its own right, broken down into knowledge, know-how and interpersonal skills. But autonomy eludes this very stabilization. It lies at the intersection of several dimensions of activity, without ever allowing itself to be reduced to a single component. As a result, the injunction to autonomy tends to take the form of a pedagogical paradox: learners are asked to be autonomous, without the conditions of possibility of this autonomy being fully explained or progressively constructed.
This injunction is often implicit. To be autonomous would mean, in a nutshell, not to depend excessively on the trainer, to know how to manage, to anticipate expectations, to take relevant initiatives. In other words, adopting the behaviors expected of a professional already socialized in the environment.
Autonomy thus becomes less an objective to be achieved than a criterion for assessing the distance between the learner and the professional norm. In this framework, learning autonomy is not explicitly engineered; it is supposed to emerge from exposure to situations, accumulated experience and confrontation with expectations in the field.
However, this approach has significant limitations. It tends to naturalize autonomy, as if some individuals are spontaneously endowed with it, while others struggle to acquire it. It ignores the processes involved in building autonomy, in particular the mechanisms of scaffolding, progressive guidance and gradual withdrawal of support. Finally, it exposes learners to a form of uncertainty, even insecurity, when they are unable to identify what is really expected of them.
Training systems play a decisive role in building, or limiting, autonomy. Their design reflects implicit choices regarding the degree of freedom granted to learners, the level of structuring of learning paths and the nature of pedagogical interactions. Yet these choices are underpinned by a constant tension between two requirements that are difficult to reconcile: securing learning and encouraging initiative.
Highly structured systems, characterized by linear progression, precise instructions and close supervision, offer a reassuring framework that is particularly well-suited to the initial phases of training. They reduce uncertainty, clarify expectations and guarantee a certain level of acquisition of fundamental skills. However, by limiting learners' room for manoeuvre, they can hinder the development of autonomy, by accustoming them to operating in an environment where decisions are largely preconceived.
Conversely, open systems, which leave plenty of room for initiative, exploration and decision-making, are often presented as more conducive to autonomy. They invite learners to become actively involved in their learning path, to build their own learning strategies and to assume the consequences of their choices. Nevertheless, this openness can prove destabilizing, particularly for learners who are less familiar with the implicit codes of training or who have limited self-regulation resources. There is a risk of widening gaps between those who manage to take advantage of this freedom and those who find it difficult to do so.
No system in itself guarantees the development of autonomy. Autonomy is not the result of maximum supervision or total freedom, but of a dynamic balance between guidance and empowerment. This balance presupposes fine-tuned engineering, capable of adjusting the level of support according to learners' needs, and organizing a gradual withdrawal of this support as skills develop.
The rise of digital educational technologies, and more recently of generative artificial intelligence, is profoundly reconfiguring learning conditions and, consequently, the ways in which autonomy is built. These tools offer unprecedented potential for individualized learning paths, immediate feedback and access to diversified resources. They enable learners to progress at their own pace, request help at any time and benefit from potentially continuous support.
From this perspective, ICTE and AI appear to be powerful levers of empowerment. They reduce direct dependence on the trainer, broaden the scope for action and encourage a form of self-direction in learning. In theory, learners can control their own learning paths, identify their needs and mobilize the appropriate resources to meet them.
However, this promise of autonomy needs to be tested against actual usage. For these same tools can also induce new, more diffuse and less visible forms of dependence.
This phenomenon, which could be described as cognitive delegation, directly calls into question the nature of the autonomy developed. Does being autonomous in a tool-intensive environment mean being able to do without the tool, or, on the contrary, knowing how to use it appropriately? Autonomy no longer resides solely in the ability to act alone, but in the ability to orchestrate external resources, both human and technological, without becoming dependent on them.
From then on, the pedagogical challenge shifts. It's no longer just a question of fostering autonomy, but of training people to be autonomous, equipped to critically integrate the contributions of technology. This implies developing specific skills: assessing the relevance of a response, identifying the limits of a tool, deciding when to use it and when not to. In other words, learning to be autonomous in a world where you are never completely autonomous.
If autonomy appears difficult to teach, oscillating between paradoxical injunction, device effects and technological dependency, its evaluation raises equally complex issues, as it eludes simple objectification.
Assessing autonomy immediately confronts the trainer with a major difficulty: its elusive nature as a direct object of observation. Unlike technical or procedural skills, which can be described, broken down and measured using relatively stable indicators, autonomy can never be seen in isolation. It manifests itself in action, through a constellation of behaviors, decision-making, contextual adjustments and implicit reasoning.
The complexity of these situations makes any attempt at objectivization a delicate task. The same behavior may be interpreted differently depending on the context in which it takes place. An initiative may be valued in one situation, but perceived as inappropriate in another. Similarly, recourse to help may be seen as a sign of excessive dependence or, on the contrary, as a sign of lucidity and responsibility. Autonomy therefore lies not in acts themselves, but in their situated relevance, i.e., in their appropriateness to the constraints and challenges of the context.
Consequently, the assessment of autonomy cannot be reduced to the verification of a series of pre-established criteria. It necessarily involves an element of interpretation, based on a global reading of the situation and the learner's position. This interpretative dimension, inherent to evaluation, is not problematic in itself, but it needs to be recognized and supervised, to prevent it from tipping over into arbitrariness.
In assessment practices, autonomy is frequently used as a synthetic criterion for making an overall judgment on a learner's level of professionalism. In such cases, it is expressed in terms such as "lack of autonomy", "autonomy in the process of being acquired" or "good autonomy", without the precise elements that led to this assessment being systematically spelled out.
This economy of precision is based on implicit frames of reference, often shared within a teaching team or professional group, but rarely formalized. It relies on representations of the "good professional", built up through experience and interaction, which serve as a point of comparison for assessing learners. Autonomy thus becomes an indicator of proximity to this standard, rather than a skill defined in terms of observable components.
Such an approach presents several risks. Firstly, it can lead to heterogeneous assessments, with each assessor using his or her own, sometimes divergent, benchmarks. Secondly, it can lead to a lack of transparency for learners, who find it difficult to understand what they are really being criticized for or expected to achieve. Finally, it can reinforce evaluation biases, linked in particular to affinities, relational styles or implicit expectations of certain profiles.
In this context, autonomy tends to function as a global judgment, condensing a plurality of elements without making them explicit. It allows us to say a lot in a few words, but at the cost of losing precision and transparency. In demanding training systems, this opacity can hinder learning by depriving the learner of clear reference points for progress.
Beyond the difficulties of objectification, the evaluation of autonomy is permeated by a normative dimension that profoundly influences its modalities. Evaluating autonomy means assessing an individual's ability to conform to a certain, often implicit, model of professional behavior. This model values qualities such as initiative, anticipation, decision-making and the ability to act without constant supervision. But it is also part of a specific organizational and cultural framework, which determines its contours.
The risk here is to confuse autonomy with conformity to a local norm. A learner may be judged autonomous if he adopts the codes and practices valued in a given department, and less autonomous if he deviates from them, even if his choices are relevant to the situation. The evaluation of autonomy thus becomes a vector of professional socialization, orienting behavior towards a certain way of doing things, sometimes to the detriment of diversity of approach.
This normative dimension can also generate paradoxical injunctions. In highly constrained environments, where room for maneuver is limited by protocols, hierarchies or traceability requirements, autonomy is simultaneously expected and restricted. The learner is called upon to show initiative, while strictly adhering to predefined frameworks. This tension can lead to discomfort, and even incomprehension, as to what is really expected.
Finally, normative evaluation of autonomy can have an impact on learners' sense of self. Being described as "not very autonomous" can be perceived as a global questioning of one's abilities, beyond the specific situations concerned. Conversely, being recognized as autonomous can reinforce a sense of competence, but also mask certain weaknesses. In both cases, the absence of explicit criteria limits the possibility of constructive, targeted feedback.
These observations call for a rethinking of the methods used to assess autonomy, recognizing its situated, interpretative and normative dimensions. Rather than seeking to objectivize it in an illusory way, we need to make it explicable, by identifying the components mobilized in situations and linking them to shared criteria. Such an evolution presupposes a shift in perspective, viewing autonomy not as a state to be measured, but as a process to be understood.
These limits, both conceptual and operational, call for us to go beyond an individualistic conception of autonomy and to think of it differently: no longer as an intrinsic property of the subject, but as a situated capacity, built in and through interactions with a given environment.
The difficulties encountered in defining, teaching and assessing autonomy stem largely from an implicit representation that sees it as an intrinsic property of the individual. To be autonomous is to be able to act alone, without dependence, by mobilizing one's own resources independently. This conception, deeply rooted in professional and educational imaginations, is based on the valorization of independence as an accomplished form of competence.
However, this vision is largely illusory when we consider the concrete conditions of professional activity. No professional, however experienced, acts in total independence. Decisions are made within organizational frameworks, based on protocols, mobilizing collective resources and adjusting to multiple constraints. Professional action is fundamentally situated and relational. It unfolds within a web of interdependencies that condition both its possibilities and its limits.
From this perspective, autonomy cannot be thought of as the absence of dependency, but as the ability to evolve in a relevant way within these dependencies. Autonomy does not consist in evading constraints, but in understanding, integrating and, to a certain extent, negotiating them. It presupposes the ability to identify available resources, to mobilize the necessary support and to adjust one's actions according to the real margins for maneuver. In other words, autonomy is inseparable from a form of situational intelligence, which goes far beyond individual initiative alone.
The evolution of professional and educational environments, marked by a densification of digital tools and decision-support systems, further reinforces this distributed dimension of autonomy. Far from being a substitute for human action, technologies are becoming integral components of it. They help to structure reasoning, provide access to information, coordinate players and trace actions.
In this context, being autonomous no longer means acting alone, but knowing how to effectively articulate a plurality of resources: human, organizational and technological. Autonomy becomes a skill of orchestration, implying the ability to choose relevant supports, assess their reliability and integrate their contributions into coherent decision-making. This instrumented autonomy cannot be reduced to technical mastery of tools; it presupposes an understanding of their logic, their limits and the effects they produce on activity.
Artificial intelligence further accentuates this transformation. By proposing answers, summaries or recommendations, it modifies the relationship to knowledge and decision-making. It can support autonomy by facilitating access to relevant information, but it can also induce a form of dependency if its use is not questioned. The challenge, then, is not to choose between autonomy and assistance, but to develop the ability to coexist with assistance, without losing control of it.
This perspective leads us to consider autonomy as an emerging property of a system of interactions, rather than as an isolated individual quality. It invites us to shift our focus from what the individual does alone, to how he or she mobilizes and coordinates the resources at his or her disposal.
Rethinking autonomy in these terms opens up new perspectives for taking it into account in training systems. It's no longer a question of aiming for abstract autonomy, which is supposed to emerge on its own, but of creating the conditions for its progressive development, by explicitly articulating the dimensions that make it up.
These different approaches converge on the same idea: autonomy cannot be decreed, it has to be built. It is neither a natural disposition, nor an automatic effect of devices, but a demanding learning process, requiring pedagogical engineering that is aware of what is at stake.
Thus redefined as a situated, distributed and constructed ability, autonomy ceases to be taken for granted and becomes a central object of pedagogical reflection. It remains to draw the necessary conclusions, by examining how training institutions can go beyond the injunction to turn it into a real lever for professionalization.
Autonomy, as it is used in skills frameworks and training programs, is both a central and deeply problematic concept. Central, because it crystallizes strong expectations in terms of professionalism, responsibility and adaptability. Problematic, because it remains largely indeterminate, difficult to teach and tricky to assess, to the point of sometimes functioning more as an implicit given than as a truly constructed skill.
Far from being an intrinsic quality of the individual, autonomy turns out to be a situated construction, dependent on contexts, available resources and the frameworks in which action takes place. It is not the same as independence, or simply taking the initiative, but refers to a more complex capacity: that of acting in a relevant way in a given environment, by mobilizing and articulating multiple resources. In this sense, it is less a state than a process, less a stable attribute than a dynamic balance between constraints and room for manoeuvre.
This re-reading invites us to go beyond the incantatory approaches that make autonomy a self-evident objective, without questioning the conditions of possibility. It leads us to recognize that the injunction to autonomy, when not accompanied by explicit expectations and appropriate pedagogical engineering, can produce counter-productive effects: opaque assessments, misunderstandings on the part of learners, and even the weakening of learning paths.
On the other hand, considering autonomy as a learning object in its own right implies making its components explicit, creating situations conducive to its development, and supporting learners as they gradually take on the responsibilities associated with it.
The rise of digital technologies and artificial intelligence is further accentuating these challenges. By reconfiguring the ways in which people access knowledge, make decisions and take action, these tools are transforming the very contours of autonomy. They offer powerful levers for increasing individual capabilities, while at the same time introducing new forms of dependency. In this context, the question is no longer simply whether individuals are autonomous, but how and with what they are autonomous. Autonomy then becomes inseparable from the ability to use tools critically, to master their contributions without suffering their effects.
At the end of this reflection, a tension remains, and it is undoubtedly irreducible. Autonomy is both a legitimate demand and an ideal that is difficult to fully achieve. It presupposes the empowerment of individuals, but also the organizational and pedagogical conditions that make it possible. It calls for both emancipation and recognition of the interdependencies that structure all human activity.
So perhaps we need to shift the question. Rather than seeking to train autonomous individuals in the sense of supposed independence, we need to train professionals capable of negotiating their autonomy, i.e. understanding its limits, exploiting its potential and assuming its responsibilities. A lucid autonomy, as it were, aware of its supports as well as its constraints.
Illustration: Autonomy: normative fiction or observable reality
Generated by AI (Canva) - Flavien Albarras
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AI usage statement - ChatGPT and Perplexity were used as assistive tools for: (a) bibliographic review assistance (locating/sorting articles and structuring reading leads), (b) rewording certain passages to improve clarity and fluency, (c) writing the abstract for this article and (d) spelling correction. Canva was used to generate the illustrative image for the article. The AI did not produce arguments or data without validation: all references were checked and no quotations were invented. The content, analyses and interpretations remain my sole responsibility.
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