Time actually devoted to learning

In the digital age, we spend an increasing proportion of our time in front of screens. Computer, smartphone, tablet... These technological tools accompany us on a daily basis, to the point of becoming for many an extension of ourselves. The figures speak for themselves: on average, a teenager spends between 4 and 5 hours a day online, taking all screens into account.(1) A considerable amount of time, which raises an essential question: in this mass of hours spent online, how much of it is actually devoted to structured, in-depth learning?

Because there's a fundamental difference between gross online time and useful learning time. Of course, we always learn something by surfing the web, interacting on social networks or playing video games. This incidental, "on-the-job" learning has its uses, but it's no substitute for focused study time, when you're fully engaged in a cognitive process to understand, memorize and put into practice in a sustained way. It's this quality time, when you're confronted with some form of intellectual effort and challenge, that really makes you progress and become more competent.

The problem is that this time is increasingly nibbled away, fragmented, competing with the quantity of online activities that constantly solicit us. E-mails, notifications, videos, news feeds... It all consumes our attention without us always being aware of it. The result: by the time it's time to concentrate on more demanding learning, our cognitive energy is already depleted, our ability to focus permanently impaired.

Faced with this observation, we can question our relationship with connected time and learn to better distinguish between the incidental and the essential. After all, it's the quality of our learning time, rather than its raw quantity, that determines our long-term personal and professional development. A salutary realization at a time when digital technology is constantly pushing back the limits of cognitive saturation.

Screen time: a misleading indicator

The statistics on our consumption of screens are impressive. According to a recent survey, children aged 1 to 6 spend up to 2 hours a day on a screen, while those aged 7 to 13 can spend up to 3 hours, all screens combined. For teenagers, this figure rises to over 5 hours a day.(1) Over a lifetime, this represents several years of cumulative time spent on the Internet, social networks, video games, mobile applications...

But this gross amount of time, massive as it is, is actually a misleading indicator when it comes to the question of learning. For not all online activities are equal in terms of cognitive engagement and educational benefits.(2) Surfing from link to link, scrolling through a news feed, watching autoplay videos... While these behaviors can provide a form of discovery and intellectual stimulation, they often remain rather passive and superficial in terms of learning.

Indeed, online time is rarely fully dedicated to study and concentration.(3) It's fragmented time, interspersed with multiple micro-activities that demand our attention to a greater or lesser degree. We move rapidly from one application to another, from one content to another, without always taking the time to digest and deepen the information received. This dispersion of attention, coupled with the practice of digital multitasking, can paradoxically be detrimental to the quality of our learning(4).

Effective learning requires sustained cognitive effort and the ability to focus on a subject or task for a sustained period of time. It's by maintaining our attention on demanding content, analyzing it in depth, actively mobilizing our knowledge, that we develop new skills. Yet this kind of engagement is undermined by the fragmentation and dispersion inherent in many online activities.

Time spent in front of screens should not be taken as a reliable measure of the actual time spent learning. It masks very different realities in terms of educational value. This invites us to question our relationship with digital technology, and to better distinguish, in the mass of our connected activities, those that really help us progress from those that merely keep us occupied in a more superficial way.(5)

Effective learning: the conditions for quality learning

To learn optimally, it's not enough to accumulate connection time or to multiply online resources.(6) Effective learning is based on a set of conditions that foster cognitive engagement and the sustainable progression of skills.(7)

• First and foremost, it is essential to have intrinsic motivation, a genuine desire to learn and develop. This motivation is the driving force behind sustained cognitive effort over time, overcoming difficulties and moments of doubt. It is nourished by a project, a clear vision of the goals to be achieved and the long-term benefits.
  
  
• Secondly, quality learning requires full concentration on dedicated activities, specifically designed to work on the targeted skills. It's not a matter of flitting between different content areas, but of engaging in a focused and structured learning process. Each activity must have a precise objective, explicit instructions and actively mobilize cognitive faculties.
  
  
• Another key factor for success is regular practice and repetition over time. You don't become an expert by passively watching a video or reading an article, but by training intensively and deliberately. It's crucial to apply one's knowledge, to practice in a variety of situations and to benefit from relevant feedback to adjust one's practice. In this way, knowledge becomes firmly rooted and becomes a real skill.
  
  
• Finally, to learn effectively, it is essential to develop metacognition, i.e. the ability to reflect on one's own learning processes. This involves becoming aware of one's cognitive strengths and weaknesses, study strategies, time management and motivation. By refining this self-knowledge as a learner, we become more autonomous and more adept at regulating our learning.

In short, quality learning mobilizes cognitive, metacognitive, motivational and strategic resources. It requires a deep and regular commitment to explicit objectives. It is only under these conditions that the time invested is transformed into real skills gains, far beyond the simple passive consumption of digital content. It's an observation that invites us to rethink our use of screens to make them more meaningful and effective from an educational point of view(7).

Obstacles to optimal learning time

In today's digital environment, a number of obstacles can stand in the way of truly qualitative and productive learning time(6).

• The first of these is undoubtedly the omnipresence of solicitations and notifications that disrupt our concentration. Smartphones, computers, tablets... All these screens generate an almost continuous flow of stimuli that capture our attention and distract us from more cognitively demanding tasks. Every alert, every message, every update acts as a small distraction that fragments our time and mental focus.
  
  
• Another major obstacle is the temptation of procrastination and immediate gratification. Faced with learning that requires sustained effort, it's tempting to turn to easier, more quickly rewarding online activities. Scrolling through social networks, watching entertaining videos, playing uncomplicated games... These behaviors offer immediate but limited satisfaction, to the detriment of engagement in more difficult but more beneficial learning tasks over the long term.
  
  
• Added to this is the risk of cognitive fatigue and saturation in the face of the mass of information available online. We have access to an almost unlimited quantity of resources, content, data... While this abundance is an opportunity for learning, it can also become overwhelming and counter-productive. Browsing from link to link, consuming fragments of scattered knowledge, can lead to mental overload and discouragement in the face of the sheer volume of knowledge to be mastered. This cognitive saturation is amplified by the often frantic, multitasking pace of online activities.
  
  
• A final obstacle lies in the growing difficulty of extracting oneself from the digital flow to settle down and concentrate on in-depth learning. Accustomed to constant stimulation and gratification, we can experience a real sense of lack and emptiness as soon as we find ourselves offline, in a demanding face-to-face encounter with knowledge to be constructed. This dependence on digital stimuli erodes our ability to tolerate the frustration and effort inherent in complex learning(8).

Faced with these multiple obstacles, it's crucial to develop strategies for preserving and optimizing in-depth learning time. This means becoming aware of the mechanisms that distract us from sustained cognitive engagement, and voluntarily setting up dedicated periods where we cut ourselves off from digital distractions. It's a question of regaining control of our attention and learning priorities, so we don't allow ourselves to be passively guided by technological devices designed more to capture our time than to bring it to intellectual fruition.

Measuring useful learning time: an issue and a challenge

While the dissociation between gross connection time and useful learning time is clear, measuring the latter remains a complex task. How can we accurately assess the quality and productivity of our e-learning activities? It's a real methodological challenge, as the factors involved are so numerous and often difficult to quantify.

To go beyond simply counting time spent in front of a screen, we need to assess the learner's actual degree of cognitive engagement. This means looking not only at the duration, but also the intensity and depth of his or her mental activity. Is he or she focused on the content, actively mobilizing knowledge, making connections and asking questions? Or is he in a more passive posture, scattered between several tasks? These are nuances that largely escape conventional quantitative measurement.

Some digital tools attempt to approach this reality of cognitive engagement, for example by offering precise monitoring of the time spent on each resource, the interactions achieved, and the performance obtained on exercises. Self-assessment systems can also help learners gauge their level of concentration, motivation and sense of progress. The development of applications for monitoring attentional faculties also opens up interesting prospects for objectifying the quality of cognitive focus.

However, despite these advances, fine-tuning the quality of learning remains a challenge, because quality is not just a collection of quantifiable parameters, it is also a matter of subjective experience, the meaning given to knowledge, and the personal integration of knowledge. These dimensions are difficult to translate into standardized metrics.

What's more, each learner is unique in his or her needs, rhythms and ways of learning(9). What will be useful time for one learner will not necessarily be so for another. Where some need lots of repetitive exercises, others will make more progress through free, independent exploration. Where some are comfortable with fragmented learning, others will need long, continuous periods of concentration. This inter-individual variability further complicates the development of universal measures of the quality of learning time.

So, while it is crucial to seek to better assess and value useful learning time, we must undoubtedly accept a degree of approximation and singularity in this measurement. The challenge is to strike a balance between generic indicators that can identify global trends, and a more personalized approach that respects the diversity of learners. Only then will we be able to develop a genuine culture of quality learning time, going beyond the raw quantity of time connected.

The effect of artificial intelligence on learning time

At a time when artificial intelligence (AI) is becoming more and more present in our lives, we might wonder about its effect on the quality of our learning time.(10) AI tools, such as virtual assistants or recommendation systems, are designed to make it easier for us to access information and help us with our daily tasks. But this ubiquitous assistance can also have ambivalent effects on our cognitive engagement and learning autonomy.(11)

On the one hand, AI can be a formidable support for personalizing learning paths, proposing resources and activities tailored to the level and needs of each learner. It can also provide immediate feedback on errors and areas for improvement, encouraging faster progress. Used wisely, AI has the potential to optimize learning time, making it more efficient and relevant.

But on the other hand, systematic recourse to AI assistance can also generate a form of cognitive dependency and intellectual passivity.(12) By relying so heavily on the suggestions and answers provided by algorithms, we can lose the habit of seeking things out for ourselves, confronting complexity and uncertainty. The risk is to develop "ready-to-think" knowledge, which doesn't take root for lack of sufficient cognitive commitment.

What's more, "A.I. assistance" can greatly influence, not to say bias, our approach, ideas and ways of apprehending an issue.(13) Its complete availability, at any time of the day or night, 7 days a week, more than that of anyone else, makes it a major competitor and can make us entirely dependent on it. By suggesting ways of thinking and ready-made solutions, AI can hinder the development of truly autonomous and creative thinking.

To make the most of AI without falling into its trap, it is crucial to learn how to use it in a reasoned and controlled way. This means understanding how it works, its strengths and limitations, and keeping a critical eye on its proposals. It also means knowing how to judiciously alternate the moments when you call on its assistance with those when you take the time to reflect and learn on your own, in order to cultivate your cognitive autonomy.

If properly integrated into a well-thought-out learning process, AI can become a valuable ally in optimizing study time, as long as you don't blindly delegate your thinking to it. It is by cultivating this intelligent complementarity between the human learner and the machine assistant that we can make connected time a truly fruitful and emancipating learning experience.

Screens and congnitive engagement

At the end of this reflection, it is clear that time spent in front of screens cannot be simplistically equated with real time devoted to learning. While digital tools offer undeniable opportunities for accessing knowledge and developing skills, their use does not in itself guarantee deep and lasting cognitive engagement.

The multiplicity of online requests, the temptation of dispersion and immediate gratification, cognitive fatigue linked to information overload... These are all obstacles that can reduce the quality of our learning time, despite prolonged connection. With the rise of AI, we also run the risk of becoming cognitively dependent on virtual assistants, which can diminish our ability to think and learn for ourselves.

Faced with these challenges, it's essential to develop greater vigilance and control over our relationship with digital technology and AI. The challenge is to strike a balance between occasional recourse to their assistance, to optimize certain tasks, and the time taken to cultivate independent thinking and sustained cognitive engagement. It's by preserving time dedicated to in-depth learning, nourished by our own thinking, that we can make connected time a real lever for personal and intellectual development.

After all, it's the quality of our cognitive presence and reflective involvement that makes our learning time worthwhile, far more than the sheer number of hours spent behind a screen. It's a salutary realization that we shouldn't allow ourselves to be passively guided by technological tools, but rather turn them into genuine allies in the service of learning that is freely consented to and fully inhabited.