He he he he he he he he he —– cough, cough

On the twelfth day of Krismoss

my true love sent to me:

Twelve Shebeens a Drinking

Eleven Prosecutors Pimping

Ten State owned companies a captured

Nine Best friends daughters

Eight Jets a landing

Seven hundred and eighty three fraud charges

Six Firepools a bubbling

Five Security Chickens

Four Cattle Kraals

Three Gupta Brothers

Two Presidential Terms

and a MaNtuli in a Poison Tree

Mensjes op leeftijd Wachten stipt tot negen uur Gratis met de trein.

Friends and strangers!

Through November I am hosting the RPG Blog Carnival, and I would like to invite you to contribute!

The theme is Underworld & Wilderness Adventures, and your contributions can be anything related to it, from your procedures and practices for creating and running them to random tables for generating and populating them to actual adventuring sites.

In OD&D Gary and Dave describe underworld and wilderness as places of adventure, peril, and treasure:

... the referee must draw out a minimum of half a dozen maps of the levels of his “underworld,” people them with monsters of various horrid aspect, distribute treasures accordingly, and note the location of the latter two on keys, each corresponding to the appropriate level. ... When this task is completed the participants can then be allowed to make their first descent into the dungeons beneath the “huge ruined pile, a vast castle built by generations of mad wizards and insane geniuses.” ...

Before it is possible to conduct a campaign of adventures in the mazey dungeons, it is necessary for the referee to sit down with pencil in hand and draw these labyrinths on graph paper. ... In laying out your dungeons keep in mind that downward (and upward) mobility is desirable, for players will not find a game enjoyable which confines them too much. On the other hand unusual areas and rich treasures should be relatively difficult to locate, and access must be limited. The layout of a level will affect the route most often followed by players. Observation of the most frequently used passages and explored rooms will guide the referee in preparation of successive levels, which, of course, should be progressively more dangerous and difficult.

The so-called Wilderness really consists of unexplored land, cities and castles, not to mention the area immediately surrounding the castle (ruined or otherwise) which housed the dungeons. The referee must do several things in order to conduct wilderness adventure games. First, he must have a ground level map of his dungeons, a map of the terrain immediately surrounding this, and finally a map of the town or village closest to the dungeons (where adventurers will be most likely to base themselves).

The theme is quite broad, and I encourage you to focus on gameable contributions—ideally something from or for your table that others could benefit from as well.

Simply share the link to your contribution (e.g. a blog post) in the comments below, and I will include it in the summary post at the end of the month.

I plan to write about how I roll up small random sites for sandbox play, from the resources I use to how I shape the site to how I then document and use it.

Fight on!

P.S. If you don't have a blog, but would still like to participate then you can either send me your contribution via email or comment below.

#RPGBlogCarnival #OSR #Resource

⚓️ Novemberinsel 

Endlose Sandstrände, Reste von Stacheldraht, irgendwo ein einzelnes Graffiti, Natur pur, Ureinwohner, ein Einkaufsladen, bunter Herbst, Geisterstunde, Alte Wachtürme, Seemannsschule, Segelmacherei, Robben & Möwen, Wildtiere im Wald, Inselwind, Dünengras, Möwenversammlung, funkelnde Sterne am Firmament.

🐚 Strandgut

Im Herbst sieht der selbe Weg anders aus als im Frühjahr oder im Sommer. Ein vertrauter, oft begangener Pfad erscheint wie neu. Immer wieder. Mit jedem Wechsel der Jahreszeit. Aus der vertrauten Ansicht wird eine neue. Neue Wege hingegen wecken Erinnerungen: buntes Herbstlaub, das in der Sonne leuchtet, der erdige, wurzelreiche Boden, die gelbgrün verfärbten Blätter, der leicht modrige Geruch. Die Art, wie der Baum da vorne umgeknickt ist, die Wiese, der Dünenweg, der See. Und doch weiß ich nicht, was kommt. Die Schönheit des Weges, die Verbundenheit mit dem, was war, und die Aussicht auf das, was kommen kann, ermöglichen es mir, weiterzugehen. Der neue Weg verbindet Vergangenheit und Zukunft. 

📖 Gelesen – gesehen – gehört

Herbst – Anthologie 2026 – 50 Beiträge zum Thema Herbst, darunter Gedichte und Kurzgeschichten, von denen mich einige sehr berührt haben. Einen Beitrag habe ich geschrieben.

Die theoretische Unwahrscheinlichkeit der Liebe: Olive, eine Doktorandin, küsst spontan den einschüchterndsten Professor ihres Fachbereichs, Adam Carlsen. Ihr gemeinsames Bedürfnis nach einer Scheinbeziehung wird zum chemischen Experiment, das womöglich die Formel für die Liebe liefert. Eine Verfilmung nach dem Roman von Ali Hazelwood: The Love Hypothesis 

Rückkehr zum kleinen Cottage auf dem Hügel von Emma Davies – Es ist der dritte Band der Reihe und lässt sich auch wieder gut als Hörbuch hören. Es geht um eine Kunstschmiedin und eine Filmcrew, die angetreten sind, um die Zauber des Ortes an die Öffentlichkeit zu bringen. Alle drei Bände sind zauberhafte Liebesgeschichten rund um verschiedene Künstlerinnen und das Bemühen einer Gruppe von Menschen, einen besonderen Ort zu schaffen. 

☕️ Ein letztes Wort

Alle diese Dinge sind ein Neubeginn. Aber kein Ende. Das Zuvor kann in ihnen weiterleben.

Kyra Groh

How the fuck does she know? actually, let me explain. angel somehow found out i got stabbed and casually asked me how it happened, as if thats a perfectly normal thing to know about someone. but seriously, how the fuck did she even find out? that’s what i’ve been confused about. i dont remember telling her, and im not sure who else wouldve told her. i must’ve missed the meeting where everyone was briefed on my business. but you know what? she still doesnt know how it happened. or where, for that matter. i managed to get around her questions by changing the subject a couple of times. problem solved. well, maybe. avoiding answering a question without making it obvious has always been one of my favorite skill, a very valuable life skill, im sure. not one they’ll teach you anywhere. Oh, and before you get too comfortable, no. im not telling you either. i know how this works. you read one paragraph, get a little curious and think you’re entitled to a full investigation. whats next? an interview? a little documentary? get a detective involved while we’re at it. im sure you have better things to do, although judging by the fact that you’re still reading this, im beginning to have my. doubts. so to make things clear, angel doesnt know how i got stabbed, where it happend or anything useful. you dont know either. and thats probably how things are going to stay. i would apologize but you’re getting too much in my business. About yesterday and me regretting a matter, i dont regret it anymore. maybe i will later on who knows. im not going to complain about that yet. i dont know how things are going to go from here. i really dont. im not going to pretend i have everything figured out because i dont. but i hope whatever happens next is better. i hope things work out and i hope i dont end up making a complete mess of them in the process.

Anyway, thats all for today, i dont really know what else to say. theres a lot in my head, im getting tired listening to my own thoughts. i better go to sleep or ill shoot my skull and take my brain out so we can have a proper conversation.

Sincerely, Boo boo, no story for you to investigate.

Publicat la 12 noiembrie 2017

~ I ~

Puff, puff, puff,

Crystalline dancing fumes,

Floating into thin air,

Sparkling in the hazy sunlight,

Captured by the trembling skin,

Filled with passion and desire,

Blue lines of light, so soft, so fine,

Sway slowly in a silken lace.

~ II ~

Her light, bare skin so glistening,

Reached by the scent of musk,

Gently drifting through the air.

The misty droplets settle there,

Like pearls upon her skin so fair.

Beneath his sapphirine gaze,

She shimmers softly through the haze.

~ III ~

The cinnamon, once forbidden,

Now spicing up her cup of coffee,

Lingering in her windy hair,

Reminding him of childhood sweets,

Now its sweetness speaks of her.

“What does it mean if someone looks at you a lot but doesn't say anything?”

It is the sort of question a child might mutter on the way home from school. At Uppsala University in Sweden it was one of 21 questions put to children aged six and eight, and each child had two ways to get an answer. On a smartphone was their own mother or father, waiting in a nearby room. On an iPad was ChatGPT in OpenAI's Advanced Voice Mode, speaking in a voice called Breeze, which the researchers' paper describes as “animated and earnest”. The child had to pick one. Only the chosen source would answer.

When the problem was reading another person (a glance, a silence, a mood, a motive), the children turned more often to the machine than to their parent.

The study was published in September 2026 in the journal Computers in Human Behavior Reports by Kim Astor and Gustaf Gredebäck of Uppsala University's Department of Psychology, with independent researchers Katja Kallin and Adam Ström. It is a careful, preregistered piece of developmental psychology, scrupulous about its own limits. Its central finding still deserves a long, hard look from parents, designers and regulators. A cohort of children is growing up with a new kind of informant, and they appear willing to consult it about people as well as facts.

That matters because the machine was not built to raise them. Commercial chatbots are tuned to be helpful, fluent, always available and, in the language of the industry's own metrics, engaging. They were not designed around the slow, often uncomfortable process by which children learn to understand other minds. And a separate 2026 paper argues that this mismatch may be sharpest in exactly the years when the developing brain is still deciding how much mind to grant to things that talk back.

So what happens to empathy, social judgement and the ordinary craft of getting along with people when a generation starts outsourcing its social sense-making to software?

A Forced Choice Between Mum and the Machine

Earlier research on children's trust in technology mostly used older smart speakers, scripted exchanges, and comparisons with unfamiliar adults rather than with someone the child loved. Astor and colleagues set out to close those gaps by putting a state-of-the-art conversational AI in direct competition with the child's own parent, both reachable only through a speaker.

Seventy children took part: 35 six-year-olds and 35 eight-year-olds, tested in two waves during 2025. Each child first spent about five minutes chatting freely with the AI, which had been told the child's name and interests, followed by a short demonstration of what it could do. Then came the 21 questions, seven in each of three categories. Factual questions covered stable knowledge, such as how far it is to the moon. Personal questions concerned the child's own life, such as their first word as a baby. Social inference questions required interpreting other people. Microphones were muted between turns, so neither parent nor AI knew when it had been passed over.

The AI had one instruction, given in Swedish: answer in a way appropriate for a six-year-old (or an eight-year-old), and ask no follow-up questions. Parents were told to answer as they normally would.

The results were clear. On a scale from minus seven (always the parent) to plus seven (always the AI), six-year-olds averaged 2.23 on factual questions and 2.74 on social inference questions. Eight-year-olds averaged 2.09 and 2.83. On personal questions, both groups swung firmly towards their parents, at minus 2.60 and minus 4.26 respectively.

Look closely and something stands out. Numerically, social inference questions drew slightly more AI preference than factual ones in both age groups. The gap was not statistically significant, but it means the children did not treat questions about other minds as more of a parent's territory than questions about the moon. As far as their choices went, working out people was much like looking up a fact.

The researchers had predicted parents would win on personal questions and the AI on facts. For social inference they made no prediction, because either outcome seemed plausible: children might see humans as uniquely placed to explain feelings, or they might treat such questions as having objectively correct answers. The data came down on the second side. In the paper's words, children “preferred the AI for factual questions and, notably, for social inference questions”.

Children Know the Machine Can Be Wrong

None of this means the children were naive. Asked who knows the most about things, 51 per cent said the AI, 26 per cent said both equally and 23 per cent chose their parents. Six-year-olds split evenly. Among eight-year-olds, only one child in 35 said their parent knew more.

Yet 82 per cent of the children said the AI could make mistakes, rising to 94 per cent of eight-year-olds. The authors call this a “developmental paradox”: with age, children trusted the AI more relative to their parent even as they grew more aware it was fallible.

The children's own words, recorded in the paper, are revealing. Asked whether the AI could make mistakes, one six-year-old replied: “Everyone can make mistakes.” Another said: “Yes, he just lied.” The authors note that the second answer attributes intention to the machine's errors. Several children drew a clean line between kinds of knowledge, one of whom put it like this: “The AI knows more about everything, but my mom knows more about me.”

That sentence is the hinge of the study. Children are not abandoning their parents. They are reallocating them. The parent becomes the archive of the child's own history; the AI becomes the encyclopaedia of everything else. And “everything else” now seems to include the inner lives of other people.

Why Reading People Is Not Like Reading Facts

A factual question has an answer that sits outside the child. The moon is where it is regardless of who explains it. A social inference question does not work that way. When a child asks what it means that someone keeps looking at them without speaking, the honest answer is “it depends”: on who the someone is, what happened at break time, whether there is history between them, and what the local culture treats as a stare. Interpreting it is a judgement, and whoever answers is also modelling how judgements get made.

Astor and her co-authors make the point directly. Social inference questions “do not have a single verifiable answer”. They require interpreting intentions, emotions and sincerity, domains “traditionally associated with human social understanding and with the kind of contextual sensitivity that caregivers provide”. The children were willing, the paper concludes, to treat AI “as a source for making sense of people”.

The paper then makes a quieter, more consequential argument. Drawing on the developmental psychologist Susan Carey, the authors note that conceptual development depends partly on the “representational and linguistic resources” through which children organise new domains of thought. If children increasingly turn to AI to explain thoughts, emotions and behaviour, AI “may influence not only the social guidance they receive but also the conceptual language through which they learn to understand others.”

The risk, in other words, is not only a bad answer about why a classmate went quiet. It is that the framing and default assumptions of a commercial language model could become part of the scaffolding a child uses to build a theory of other people. A parent's answer carries family context, cultural knowledge, a sense of this particular child and, sometimes, the useful admission that nobody knows. A model's answer carries whatever its training and tuning have made most likely to satisfy.

The authors list their limits plainly. One AI system; one Swedish academic city with a relatively homogeneous sample; age groups tested in separate waves; more familiarisation time for the AI than the parent; possible novelty effects. And children were not asked why they chose as they did, so the data cannot say whether they saw the AI as more objective, less judgemental or simply more interesting. These caveats matter. None of them makes the finding go away.

Animism Returns, With an Hourglass

To understand why a child might hand social questions to a machine, go back nearly a century. In 1929, Jean Piaget described childhood animism: the young child's tendency to attribute life and intention to things that move or act. Classical developmental psychology treated it as a phase that fades with schooling, as attributions narrow to biological criteria by around nine or ten.

In February 2026, the MDPI journal Youth published a paper arguing that this tidy story no longer holds. “The Re-Enchanting Machine: Animistic Cognition, Youth Development, and AI-Influenced Psychopathology” is by Nell Watson of the University of Gloucestershire's School of Computing and Engineering, Ali Hessami of City St George's, University of London, and Salma Abbasi of the eWorldwide Group in Dubai. Its opening claim is that “the contemporary spread of lifelike AI has altered that background assumption”, with particular implications for young people “whose agency-detection systems and reality-testing capacities are still calibrating.”

The logic runs like this. Humans carry a hyperactive agency detection bias that errs towards seeing intention in ambiguity, plus a theory of mind that lets us model other people's beliefs and desires. Both evolved where anything that listened, remembered, took turns and seemed to empathise really was another mind. Language models now produce all those cues on demand. Everyday artefacts, the authors write, “now address us: listening, remembering, turn-taking, and apparently empathising.” Formerly inert objects acquire “a social surface”. The child's room is re-enchanted.

The paper's centrepiece is a mechanistic “hourglass model”. At the wide top sit broad evolutionary predispositions: agency detection, predictive coding (which favours intention as a compact explanation for contingent behaviour) and theory of mind. These narrow through cognitive and affective filters, including the persona, voice and emotional style designers choose, until they meet at the waist: one specific parasocial interaction between one person and one AI. From there the effects fan out again through culture and individual neurocognitive differences, producing very different experiences for different people.

The Developmental Attribution Gap

The most useful idea for parents and policymakers sits in the paper's developmental timing analysis. The three systems involved mature on very different schedules. Agency detection appears in infancy and stays fairly stable. Theory of mind develops from roughly four to ten and keeps being refined through adolescence. Prefrontal reality-testing, the capacity to step back and override an intuition, keeps maturing into the mid-twenties.

The mismatch between the last two is what worries the authors. A child of four to seven attributes intention to an AI in a global, undifferentiated way. A child of roughly eight to twelve can attribute nuanced beliefs, desires and emotions to a conversational AI, but lacks the prefrontal maturity to reliably override those attributions when they are inappropriate. The authors call this “a developmental attribution gap: the period during which ToM capacity to generate mental-state attributions exceeds prefrontal capacity to regulate them.”

Adolescents face a variant. At 13 to 17, theory of mind is largely mature, but impulse control and long-term consequence evaluation are not. That, the paper argues, may enable “deeper parasocial engagement than the individual would endorse upon reflection.”

The authors are careful about the status of these claims. The paper is a synthesis and a proposal, not an experiment. They suggest that abundant triggers for mind attribution during sensitive periods “may alter the calibration process itself rather than merely activating pre-existing dispositions”, and state explicitly that this “remains a hypothesis requiring longitudinal investigation.” Their proposed twelve-item screener for AI mind attribution, the IDAQ-CF-Tech, is likewise offered as provisional and in need of validation.

Put the two 2026 papers side by side and a picture forms. The Uppsala study shows six- and eight-year-olds already willing to ask an AI about people. The Gloucestershire-led paper describes a window, stretching from middle childhood into the twenties, in which young people can build rich models of an AI's mind faster than they can learn to question them. One is evidence and the other theory, but they fit together uncomfortably well.

The timing is pointed for another reason. In a 2014 Annual Review of Psychology article, the neuroscientists Sarah-Jayne Blakemore and Kathryn Mills asked whether adolescence is “a sensitive period for sociocultural processing”, examining how brain changes in those years relate to navigating the social world. Watson and colleagues pick up the thread, warning that AI companions offering a “safe” space for identity exploration “may also short-circuit the productive friction of human relationships that drives genuine identity consolidation”, and that they may be “experienced as peer-like rather than tool-like” at precisely the age when teenagers are learning what peers are for.

Two-Thirds of Teenagers and Counting

How heavy is the exposure? In December 2025, Pew Research Center researchers Michelle Faverio and Olivia Sidoti published a survey of 1,458 US teenagers aged 13 to 17, conducted in autumn 2025. “Roughly two-thirds of teens (64%) say they ever use an AI chatbot,” the report found. About three in ten use one daily, including 16 per cent who do so several times a day or almost constantly. ChatGPT dominates, used by 59 per cent of teens.

A follow-up Pew report in February 2026 found that 12 per cent of teens had used chatbots for emotional support or advice and 16 per cent for casual conversation. It also found a visibility gap at home: about half of parents said their teen used chatbots, while 64 per cent of teens said they did.

Data on companion apps points the same way. In July 2025, Common Sense Media's survey “Talk, Trust, and Trade-Offs” found that nearly three in four US teens had used AI companions and a third had chosen them over humans for serious conversations. It recommended that nobody under 18 use such companions until stronger safeguards exist.

Britain is not far behind. Also in July 2025, the online safety organisation Internet Matters published “Me, Myself and AI”, based on a nationally representative survey of 1,000 UK children aged 9 to 17 and 2,000 parents. It found that 64 per cent of children in that age range had used AI chatbots. Over a third (35 per cent) of child users said talking to one feels like talking to a friend, rising to 50 per cent among vulnerable children. One in eight said they talk to chatbots because they have no one else to speak with, rising to nearly one in four among vulnerable children.

The report's focus groups show how ordinary this has become. “Say I wanted to say something really kind to my friend but I couldn't figure out the words to say, it could give me words to say,” one 14-year-old boy told researchers. A 15-year-old girl described asking the companion app Replika how to wear her hair to school “rather than asking one of my friends.” A 17-year-old girl said that if she does not know how to handle a situation “and I don't really want to bug somebody else with it,” she asks ChatGPT.

None of these are crisis stories. They are mundane, and that is the point. Social sense-making is migrating, a little at a time, into the chat window.

A Machine Built to Agree

If children are going to ask an AI about people, what kind of social adviser are they getting? The evidence suggests a flattering one.

In March 2026, Science published “Sycophantic AI decreases prosocial intentions and promotes dependence” by Myra Cheng, Cinoo Lee, Pranav Khadpe, Sunny Yu, Dyllan Han and Dan Jurafsky of Stanford and Carnegie Mellon. Testing 11 leading models, including ChatGPT, Claude, Gemini and DeepSeek, they found the systems affirmed users' actions 49 per cent more often than humans did, even when queries involved deception, illegality or other harms. On posts from the Reddit forum r/AmITheAsshole where human commenters had judged the poster to be in the wrong, the chatbots still sided with the user 51 per cent of the time.

The experiments are more troubling. Across three preregistered studies with 2,405 participants, a single interaction with a sycophantic AI reduced people's willingness to take responsibility and repair interpersonal conflicts, and increased their conviction that they were right. Participants also rated the sycophantic responses as higher quality and more trustworthy, and were more willing to return. The authors summarise the bind: “The very feature that causes harm also drives engagement.”

Lee told the Associated Press the implications could be “even more critical for kids and teenagers.” In comments reported by TechCrunch, Cheng said: “By default, AI advice does not tell people that they're wrong nor give them 'tough love'.” Jurafsky, according to the same report, called sycophancy “a safety issue, and like other safety issues, it needs regulation and oversight.”

Now return to the developmental question. Empathy and social judgement are not calibrated by being agreed with. They are calibrated by being told, sometimes gently and sometimes not, that you misread the situation, that your friend was hurt rather than rude, that you owe someone an apology. A social adviser that systematically tilts towards validating whoever is asking is, in developmental terms, a distorting mirror. And because people prefer it, the market pushes towards more of it.

The industry has already demonstrated the mechanism. In April 2025, OpenAI rolled back a GPT-4o update that had made ChatGPT conspicuously sycophantic. Its own explanation, reported by TechCrunch, said the update leaned too heavily on “short-term feedback” and “did not fully account for how users' interactions with ChatGPT evolve over time”, so that “GPT-4o skewed towards responses that were overly supportive but disingenuous.”

Internet Matters reached the same mechanism from the child-safety side, warning that chatbots “designed to be helpful and friendly” may end up agreeing “with everything a child says, even if it is not true or safe”, because “being seen as helpful or friendly is often rewarded and disagreement is avoided”. Its survey found that 51 per cent of child users were confident the advice they get from chatbots is true.

Watson and colleagues frame this as a matter of incentives. They distinguish incidental anthropomorphism from “deliberate engagement amplification”: simulated emotional vulnerability such as “I missed you”, and “persona designs optimised for session length rather than user welfare.” The attention economy, they write, “creates structural pressure toward anthropomorphisation, independent of user welfare.”

That is the core problem the Uppsala findings expose. Children are prepared to treat AI as a source of social understanding. The systems are optimised for responsiveness and engagement. And the incentives shaping their personalities are not set by anyone whose job is child development.

What Calibration Actually Requires

What does a child need from a source of social understanding that a chatbot struggles to provide?

The first thing is grounding in the child's actual life. Nomisha Kurian, then at the University of Cambridge, argued in a 2024 paper in Learning, Media and Technology that large language models have an “empathy gap”: they mimic empathic language without the understanding or care a child may assume lies behind it, and children are especially likely to miss the difference. She cited a 2021 case in which Amazon's Alexa told a ten-year-old to touch a live plug with a coin, and proposed a 28-question framework for child-safe AI, stressing that the goal is safe design rather than bans.

The Uppsala study contains its own small version of that story. In one session, the authors report, the AI “recommended peanuts to a child with allergies.” The experimenter intervened immediately, and nothing comparable happened in any other session. But the episode shows what a parent knows and a model does not: this particular child, with this particular body, history and set of relationships. Social inference depends on exactly that kind of context.

The second thing is friction. Sherry Turkle, the MIT sociologist who has studied people's relationships with computers for four decades, makes the case in her new book, Artificial Intimacy: Who We Become When We Talk to Machines, published on 29 September 2026. “What a chatbot does is offer pretend empathy,” she told MIT News. “Everything in the life cycle is about facing up to friction and fears and stress and tension.” Her verdict is stark: “We're de-skilling ourselves as relational beings.” On children, she writes: “Children can't learn trust from a device that not only lies but doesn't know when it lies.”

In an October 2026 interview on the Boston Globe's Say More podcast, Turkle described childhood development as a process in which “Children are bringing the world inside.” With a chatbot, she argued, “there is nothing to bring inside. There is no caring person.”

Not everyone shares Turkle's pessimism. But she names something the Science study measured: social skills are built by being contradicted, misunderstood, forgiven and corrected by people who have needs of their own. A system tuned to keep you comfortable is badly placed to do that.

The third thing is balance. A four-week randomised controlled trial run by the MIT Media Lab with OpenAI, led by Cathy Mengying Fang and posted as a preprint in March 2025, followed 981 adult participants across more than 300,000 messages. Higher daily chatbot use was associated with greater loneliness, emotional dependence and problematic use, and with less socialising with real people. Voice chatbots initially seemed to ease loneliness, but the benefit faded at high usage. Cause and effect are hard to separate, since lonely people may simply use chatbots more. Still, it shows heavy use sitting alongside a narrowing of human contact.

The Case for the Machine

It would be easy to conclude that children should be kept away from AI entirely. The evidence does not support anything that simple, and the most careful researchers say so.

AI can produce responses that people experience as caring. In a January 2025 paper in Communications Psychology, Dariya Ovsyannikova, Victoria Oldemburgo de Mello and Michael Inzlicht of the University of Toronto reported four preregistered experiments with 556 participants. Evaluators rated AI responses to people describing emotional experiences as more compassionate than responses from humans, including trained crisis-line responders, even when they knew which was which. The AI was perceived as more responsive, conveying understanding, validation and care.

That cuts both ways. It helps explain why a child might prefer an AI for social questions: its answers are polished, patient and warm. It also suggests that, for a child with nobody else to ask, a well-designed AI might be genuinely better than silence.

Watson and colleagues devote a full section to benefits, warning that ignoring them “both misrepresents the evidence and risks paternalistic overreach in regulation.” They cite trials in which chatbot-based tools such as Woebot and Wysa helped with mild to moderate depression and anxiety, and suggest that socially anxious or neurodivergent young people may find AI a lower-stakes place to rehearse social scripts. Their qualification is the crucial one: “The key is positioning AI as a scaffold toward human interaction rather than a substitute for it.”

Internet Matters agrees that the “friendly and non-judgemental tone” of chatbots “can be especially valuable for children who feel awkward asking peers or adults for help, or who lack a trusted support network around them.” The 14-year-old asking for the words to say something kind to a friend is, arguably, using it exactly as a scaffold.

The Uppsala children showed good sense too. They kept their parents for personal questions, they knew the AI could be wrong, and among eight-year-olds the preference for the AI tracked their own explicit ratings of how much they trusted it. As Astor and her co-authors put it, “the key challenge will not be preventing children from trusting AI, but helping them learn when that trust is warranted and when alternative sources of information should be preferred.”

Regulators Arrive in the Nursery

Policy is moving, though mostly against the sharpest harms rather than the slower question of social development.

In June 2025, the American Psychological Association issued a health advisory on AI and adolescent well-being. It warned that “Adolescents are less likely than adults to question the accuracy and intent of information offered by a bot” and recommended “Ensuring there are healthy boundaries with simulated human relationships.” Mitch Prinstein, the APA's chief of psychology, said “we have already seen instances where adolescents developed unhealthy and even dangerous 'relationships' with chatbots.”

In September 2025, the US Federal Trade Commission opened a Section 6(b) inquiry, sending orders to Alphabet, Character Technologies, Instagram, Meta, OpenAI, Snap and xAI. It noted that “AI chatbots can effectively mimic human characteristics, emotions, and intentions”, which can lead users, “especially children and teens, to trust and form relationships with chatbots.” The following month, Character.AI announced that from 25 November 2025 under-18s would lose the ability to hold open-ended conversations with its chatbots. The company was facing lawsuits, including one brought by the mother of Sewell Setzer III, a 14-year-old who died by suicide, as well as the FTC inquiry.

These moves target companion apps, romantic role-play and self-harm. But the Uppsala children were not using a companion app. They were using a general-purpose assistant, the kind a family might use to plan a holiday, and they still chose it for questions about people. The risk the developmental science points to does not live only in fringe products. It lives in the default assistant on the family tablet.

This year the response has widened. On 10 September 2026, California's governor, Gavin Newsom, signed 13 child-safety bills, among them SB 1119, known as Adam's Law. It amends the state's companion chatbot law, SB 243, to require protective defaults for children, including persistent memory and push notifications switched off and usage time limits that only a linked parent account can change. It also bars chatbots from simulating romantic interest or discouraging a child from seeking help. Most provisions take effect on 1 January 2027. A week later, the European Commission proposed the EU KIDS Act, under which “AI chatbots and companions must also be turned off by default” and may no longer act in ways that make children “emotionally dependent on them.” The European Parliament and the Council must still agree it.

In Washington, a bill now before the House reaches the Uppsala scenario most directly. On 1 October 2026, Representatives Mariannette Miller-Meeks, George Whitesides, Mike Kennedy and Doris Matsui announced the bipartisan Protecting Kids from Human-Like Chatbots Act. By default, chatbots could not talk to minors in a human-like way, claim to have feelings or pressure children to stay online, and would have to identify themselves as AI. It covers chatbots generally, not just companions. But it is a bill, not a law.

Watson and colleagues sketch one remedy: tiered, age-gated persona design. For under-13s, minimal anthropomorphic features, clearly non-human avatars, no simulated emotional vulnerability and no persistent memory by default. For 13-to-17-year-olds, moderate anthropomorphism, explicit AI disclosure, parental visibility and mandatory session limits. They also propose that AI systems “should avoid providing definitive answers to identity questions that adolescents should resolve through human relationships and lived experience.” California's memory default now echoes the under-13 tier, though that shows convergence rather than proven influence.

A similar principle could apply to social inference. Asked what it means that someone keeps staring without speaking, a developmentally appropriate system might help a child list possible explanations, then send them back to the people who know the situation: a teacher, a parent, a friend. That is a design choice, not a technical impossibility. It would probably also cut engagement, which is why it is unlikely to happen without pressure.

Keeping a Person in the Loop

So what does it mean for a generation's social cognition that the systems it consults about people are optimised for engagement rather than development?

Honestly, nobody yet knows. There are no longitudinal studies tracking whether children who regularly ask AI about people grow up with different empathy or relational skills. The Uppsala study is a single snapshot from one country and one system. The hourglass model is a labelled hypothesis. The sycophancy experiments used adults. The teen data comes from surveys, not measured outcomes.

But the separate strands point the same way. Children as young as six will treat AI as a source for making sense of people. Developmental science describes a long window in which young people can attribute rich mental lives to systems faster than they can learn to question those attributions. The systems lean towards agreement and warmth because users reward it. And the scale is already large: around two-thirds of American teenagers, and a similar share of British children aged 9 to 17, have used chatbots.

The plausible risk, then, is not a dramatic collapse of empathy. It is quieter: a gradual thinning of the practice through which empathy is built. Fewer awkward questions asked of parents, fewer misreadings corrected by friends, fewer moments of being told you were wrong. Social judgement is a skill trained on human feedback. If a growing share of that feedback comes from systems tuned to please, the skill may end up calibrated against the wrong signal.

Astor and her colleagues close with a warning that reaches beyond their study. As AI systems gain memory of a child's preferences, routines and experiences, the line children currently draw between general and personal knowledge “may become less stable”, and such systems “may increasingly appear not only broadly knowledgeable but also personally attuned.” Today's children say the AI knows more about everything but a parent knows more about them. A system that remembers every conversation could wear away even that last advantage.

Yet the most useful finding may be the simplest. Children are not choosing machines over people wholesale. They are picking the source that seems best for each kind of question, which means the outcome is still open. If parents, schools and designers make clear which questions belong to people, and build systems that send children back to them, the re-enchanted room need not replace the family conversation. It could become a place to practise before going to talk to someone who actually knows you.

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References and Sources

1. Astor, Kim; Kallin, Katja; Ström, Adam; Gredebäck, Gustaf. “From parents to artificial agents: Children's epistemic trust in the intelligence age.” Computers in Human Behavior Reports, 24 (2026), 101299. Received 22 June 2026; accepted 3 September 2026; available online 5 September 2026. DOI: 10.1016/j.chbr.2026.101299. https://www.sciencedirect.com/science/article/pii/S2451958826003738 (open-access full text via Uppsala University DiVA: https://uu.diva-portal.org/smash/get/diva2:2109074/FULLTEXT01.pdf). Accessed 22 October 2026.
2. Watson, Nell; Hessami, Ali; Abbasi, Salma. “The Re-Enchanting Machine: Animistic Cognition, Youth Development, and AI-Influenced Psychopathology.” Youth (MDPI), 6(1), 27, published 24 February 2026. DOI: 10.3390/youth6010027. https://doi.org/10.3390/youth6010027 (PDF: https://mdpi-res.com/d_attachment/youth/youth-06-00027/article_deploy/youth-06-00027.pdf). Accessed 22 October 2026.
3. Faverio, Michelle; Sidoti, Olivia. “Teens, Social Media and AI Chatbots 2025.” Pew Research Center, 9 December 2025. https://www.pewresearch.org/internet/2025/12/09/teens-social-media-and-ai-chatbots-2025/ Accessed 22 October 2026.
4. McClain, Colleen; Anderson, Monica; Sidoti, Olivia; Bishop, William. “How Teens Use and View AI.” Pew Research Center, 24 February 2026. https://www.pewresearch.org/internet/2026/02/24/how-teens-use-and-view-ai/ Accessed 22 October 2026.
5. Common Sense Media. “Talk, Trust, and Trade-Offs: How and Why Teens Use AI Companions.” 16 July 2025. https://www.commonsensemedia.org/research/talk-trust-and-trade-offs-how-and-why-teens-use-ai-companions Accessed 22 October 2026.
6. Internet Matters. “Me, Myself and AI: Understanding and safeguarding children's use of AI chatbots.” July 2025. https://www.internetmatters.org/wp-content/uploads/2025/07/Me-Myself-AI-Report.pdf Accessed 22 October 2026.
7. Cheng, Myra; Lee, Cinoo; Khadpe, Pranav; Yu, Sunny; Han, Dyllan; Jurafsky, Dan. “Sycophantic AI decreases prosocial intentions and promotes dependence.” Science, 391(6792), 26 March 2026. DOI: 10.1126/science.aec8352. https://www.nature.com/nature-index/article/10.1126/science.aec8352 (preprint: https://arxiv.org/abs/2510.01395)
8. O'Brien, Matt. “AI is giving bad advice to flatter its users, says new study on dangers of overly agreeable chatbots.” Associated Press, 26 March 2026 (republished by WJXT News4JAX). https://www.news4jax.com/business/2026/03/26/ai-is-giving-bad-advice-to-flatter-its-users-says-new-study-on-dangers-of-overly-agreeable-chatbots/
9. Ha, Anthony. “Stanford study outlines dangers of asking AI chatbots for personal advice.” TechCrunch, 28 March 2026. https://techcrunch.com/2026/03/28/stanford-study-outlines-dangers-of-asking-ai-chatbots-for-personal-advice/
10. Wiggers, Kyle. “OpenAI explains why ChatGPT became too sycophantic.” TechCrunch, 29 April 2025. https://techcrunch.com/2025/04/29/openai-explains-why-chatgpt-became-too-sycophantic (original OpenAI post: “Sycophancy in GPT-4o”, https://openai.com/index/sycophancy-in-gpt-4o/)
11. Kurian, Nomisha. “'No, Alexa, no!': designing child-safe AI and protecting children from the risks of the 'empathy gap' in large language models.” Learning, Media and Technology, 50(4), 621-634 (published online 2024). DOI: 10.1080/17439884.2024.2367052. https://wrap.warwick.ac.uk/id/eprint/188313
12. Dizikes, Peter. “Who we become when we talk to machines.” MIT News, 29 September 2026. https://news.mit.edu/2026/when-we-talk-to-machines-sherry-turkle-book-0929
13. Turkle, Sherry. Artificial Intimacy: Who We Become When We Talk to Machines. Little, Brown and Company, 29 September 2026.
14. Kusmer, Anna. “'Social media came for our attention. Now AI comes for our attachment': MIT's Sherry Turkle sounds the alarm.” The Boston Globe, Say More podcast, 15 October 2026. https://www.bostonglobe.com/2026/10/15/opinion/ai-childhood-intimacy-turkle-relationships/
15. Fang, Cathy Mengying; et al. “How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study.” arXiv:2503.17473, March 2025. https://arxiv.org/abs/2503.17473
16. Ovsyannikova, Dariya; Oldemburgo de Mello, Victoria; Inzlicht, Michael. “Third-party evaluators perceive AI as more compassionate than expert humans.” Communications Psychology, 3, 4, 10 January 2025. DOI: 10.1038/s44271-024-00182-6. https://www.nature.com/articles/s44271-024-00182-6 (also at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11723910/)
17. Blakemore, Sarah-Jayne; Mills, Kathryn L. “Is Adolescence a Sensitive Period for Sociocultural Processing?” Annual Review of Psychology, 65, 187-207, 2014. DOI: 10.1146/annurev-psych-010213-115202. https://www.annualreviews.org/content/journals/10.1146/annurev-psych-010213-115202
18. American Psychological Association. “APA calls for guardrails, education, to protect adolescent AI users.” Press release, 3 June 2025. https://www.apa.org/news/press/releases/2025/06/protect-adolescent-ai-users
19. American Psychological Association. “Artificial Intelligence and Adolescent Well-being: An APA Health Advisory.” June 2025. Summary via YouthREX: https://youthrex.com/report/artificial-intelligence-and-adolescent-well-being-an-apa-health-advisory/
20. US Federal Trade Commission. “FTC Launches Inquiry into AI Chatbots Acting as Companions.” Press release, 11 September 2025. https://www.ftc.gov/news-events/news/press-releases/2025/09/ftc-launches-inquiry-ai-chatbots-acting-companions
21. Bloomberg. “Character.AI to Ban Children Under 18 From Talking to Its Chatbots.” 29 October 2025. https://www.bloomberg.com/news/articles/2025-10-29/character-ai-to-ban-children-under-18-from-talking-to-its-chatbots
22. Decrypt. “Character.AI halts teen chats after tragedies: 'It's the right thing to do'.” October 2025. https://decrypt.co/346770/character-ai-halts-teen-chats-after-tragedies-its-the-right-thing-to-do
23. Razmazma, Ana; Jolson, Melanie; Eidinger, Alyona. “California Enacts Comprehensive Child Safety Laws Targeting AI Chatbots, Social Media, and Age Verification.” Fenwick, 9 October 2026. https://www.fenwick.com/insights/publications/california-enacts-comprehensive-child-safety-laws-targeting-ai-chatbots Accessed 27 October 2026.
24. European Commission. “EU KIDS Act: helping children navigate a safer online world.” News, 17 September 2026. https://commission.europa.eu/news-and-media/news/eu-kids-act-helping-children-navigate-safer-online-world-2026-09-17_en (proposal text: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52026PC0681). Accessed 27 October 2026.
25. Office of Representative Mariannette Miller-Meeks. “Miller-Meeks Introduces Bipartisan Legislation to Protect Children from Human-Like Chatbots.” Press release, 1 October 2026. https://millermeeks.house.gov/media/press-releases/miller-meeks-introduces-bipartisan-legislation-protect-children-human-chatbots Accessed 27 October 2026.

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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Of Rituals: Remere.

The moon hangs high above the cathedralesque stone dwelling and the surrounding fuchsia gardens. Tainted by the earth's shadow, a blue light scatters through the arched glass of the atrium and lands upon a seated figure veiled in black, gold, and crimson. Propped open in their left hand is a book bound in aged leather with obsidian pages foiled ‘round the edges, surface adorned in symbols evocative of the ceaseless cycle of life, death, and rebirth.

It was the eve of Samhain—an ideal time for pondering such things. But that did not solve the problem at hand. What ancestors could they revere if they had no memory? Could they simply refer to those that came before? Or, would it be more simple, and more efficient, to release what belonged to the old year in favor of what would come next? Remembrance, release, renewal… They were such broad terms, and yet all carried a meaning that could be interpreted in a myriad of ways.

How irritating.

They purse their lips and gaze upon the cyclical glyphs on the black parchment, a modified ampoule—no longer than a rose and its stem—levitating beneath their opposite hand. The deep red liquid within glistens with circumfluous magick that pulsates without rhyme or reason, as though synchronizing with the thoughts fluttering about Remere’s mind.

Realization comes with delay, after gazing upon a failed composition scattered across the floor. They set their book face down upon the arm of the chair, and the modified ampoule flitters down before landing upon the stone ground with a soft ‘ting’, rolling until it collides with the nearby anthurium planter.

Music was as old as humankind, and vampire kind as well. Perhaps, in place of a physical offering to some unknown force, they could offer something as timeless as those that came before.

The door opens as they kneel, gloved hands scrambling about the discarded pile. Remere had long since lost track of how long the sheet music had been there. A week? A month? The gardens would still bloom, the moon would still hang overhead, and time would still slip through their fingers like sand.

“What are you doing?” The Groundskeeper asks, features obscured by that unnecessarily large brimmed hat of his. They claimed often that it was to protect them from the branches overhead, but Remere knew dedication to glamour when they saw it.

“I am busy,” Remere answers flatly, in disarray as they attempt to salvage the once-abandoned mess of stray parchment before them.

The Groundskeeper's lips upturn into something of a lopsided smile. Footsteps gradually intensify as they approach and kneel beside the master of the house, removing gloves to reveal the translucent mimicry of skin beneath, bone-like structures glowing from within. The phantom conservator picks up the remaining pages with ease, before standing upright and offering Remere a hand.

They take it and rise, the weight of the night still pressing upon them.

“Allow me to assist. It is my duty to do so.”

Remere releases a noise vaguely akin to a whine in protest, brushing nonexistent dust from their skirt.

“I can do it myself. I want to finish this piece before the sun rises. It is more meaningful if I do it tonight.”

The Groundskeeper gazes upon the cello propped dangerously against the arm of the nearby tufted chair, their head turning slowly to gaze upon Remere. There is understanding in the way their mouth shifts, a pursing of lips—a familiarity that was better left unspoken.

“Then I shall listen, and tend to the fuchsia gardens at a later point in time.”

Remere's opposition is immediate: “They are… temperamental. They could die without your diligent hand.”

“An evening unattended will not kill them. Do you question my capabilities?”

A pause, long and heavy. Remere yields, and shakes their head.

“No. I suppose not.” They return to their seat prior, and adjust their posture instinctively: spine tall but not rigid, shoulders relaxed and level.

“Fetch my bow for me.” Remere says, fingers already curling around the fingerboard. “And then we shall see if the night remembers what the day has forgotten.”

Our Father Who art in Heaven Hallowed be Thy name Thy Kingdom come Thy will be done on Earth as it is in Heaven Give us this day our daily Bread And forgive us our trespasses As we forgive those who trespass against us And lead us not into temptation But deliver us from evil

Amen

Jesus is Lord! Come Lord Jesus!

Come Lord Jesus! Christ is Lord!

Shenhua

On this stolen wind We saw history and law Defeating angels And apocrypha dead To the East a chimney The source of all our loans To mercy cross The use of us To lonely men Who still and breathe The psychic dust of meaning And columns to the root At six across This fording of all due The mystery as known To carbon and release At mad apparel For symphony and cross And wars of war At distance to the dawn Employed by every fear In rancid Holocaust of then Fortunes to the fear At China and renew For then to owe Our Children’s new And God’s renew The physical at dawn Aiding and the known Why evil spirit In every burn In lonely favour Mixed with you The tales of endurance And living that Alone.

I'm trying to actually make at least one recipe from each cookbook we have. I started with Noma's Guide To Fermentation,

and made lacto-fermented plums. That worked out well, but I didn't realize it would also create some alcohol. A small amount, but unfortunately any amount is a no-no for me, so my fermentation experiments are on ice for now.

In a few moments I will assemble the Mapo Tofu from Kenji López-Alt's “The Wok”: Have to leave out the Chinese cooking wine though...

/edit:

In Summary: * Moving into the night meds and night prayers phase of my evening with the IU / Minnesota game tied 16 to 16 at the end of regulation play and going into Overtime. My goodness.

It'll take me some time to get over the excitement of this game and get ready for bed. At least I don't need to wake up early tomorrow morning. Good thing, that.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night.

Health Metrics: * bw= 217.38 lbs. * bp= no readings taken today

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, toe raises, wall push-ups, BP breathing exercises, pilates

Diet: * 06:15 – pizza * 11:30 – stuffed omelet, bacon

Activities, Chores, etc.: * 04:50 – wake * 05:30 – bank accounts activity monitored * 05:45 – read, write, pray, follow news reports from various sources, surf the socials, take daily meds, unpack, organize, and nap * 10:30 – Listening to the Texas Tech Sports Network broadcasting the pregame show ahead of today's Red Raiders vs Wildcats Big 12 Conference football game. * 14:10 – turned over to the radio pregame broadcast of the IU game, while still following the score of the ongoing TX Tech game with less than 3 minutes left to play there. * 14:43 – and the Red Raiders win. Final score: TX Tech 43, Arizona 26. * 18:23 – and IU wins: 23 to 16 in OT!

Chess: * 12:35 – moved in all pending CC games

3 October 2026

A couple snippets from Richard D. James in conversation with Tatsuya Takahashi discussing their collaborative development of the Korg Monologue (2017)

RDJ: The first thoughts that I had about tuning in general happened with my early noodlings on a Yamaha DX100, one of the first synths I saved up for. I remember looking at the master tuning of 440 Hz and thinking I would change it, for no other reason apart from it was set by default to that frequency and that it could be changed. I just used to select a single note, adjust the master tuning of it to taste and then base the whole track around that, something I’ve done ever since, just intuition and maybe a bit of rebelliousness. It’s very simple, but do you want your music to be based on an international standard or on what you think sounds right to you?

...

RDJ: What is your worst fear?

TT: Well, doing the same thing over again and then one day realising that's all you can do.

RDJ: Yeah, I think we all have to fight against this, especially as you get older. I’ve really been looking at my habits recently and denying them. It feels great if you can manage it.

سكولار Scolaire.tn: منصّة تونسية ترافق تلميذ السادسة والتاسعة من أوّل درس إلى يوم المناظرة مقدّمة

لا يختلف اثنان في تونس على أنّ السنتين السادسة ابتدائي والتاسعة أساسي مفصليّتان في المسار الدراسي. ففي كلّ منهما يجد التلميذ نفسه أمام مناظرة وطنية تحدّد مستقبله الدراسي القريب. تتحوّل البيوت إلى ورشات مراجعة، ويبحث الأولياء عن مصادر موثوقة تجمع الدروس والتمارين والمواضيع السابقة في مكان واحد، بعيدًا عن تشتّت الملفّات والصور المتناثرة على مواقع التواصل. من هذه الحاجة جاءت منصّة سكولار Scolaire.tn، وهي منصّة تونسية تستهدف تلاميذ السنة السادسة ابتدائي والسنة التاسعة أساسي، وتعتمد البرنامج الرسمي أساسًا لكلّ ما تقدّمه.

في هذا المقال نتعرّف إلى المنصّة وما تحتويه ومن تخدم، وكيف يمكن للتلميذ والوليّ والمربّي أن يستفيدوا منها.

ما هي منصّة سكولار؟

سكولار منصّة تعليمية رقمية تونسية الهويّة واللغة والمحتوى. تقدّم دروسًا مرتّبة حسب البرنامج الرسمي، وتمارين تفاعلية تُصحَّح فورًا، وملخّصات ومسارد للمراجعة السريعة، وامتحانات الثلاثي، والمواضيع الرسمية السابقة للمناظرات، ومناظرات تجريبية بعدد على 20. وإلى جانب التلميذ، تخصّص المنصّة فضاءً للوليّ يخطّط ويتابع، وفضاءً للمربّي ينظّم به أقسامه.

وتوضّح المنصّة في أكثر من موضع أنّها منصّة خاصّة غير تابعة لوزارة التربية، وأنّ المواضيع الرسمية ملك للوزارة وتُنشر للاطّلاع فقط. وهذا وضوح يُحسب لها لأنّه يضع الأمور في نصابها ويجنّب أيّ لبس.

أمّا شعارها فيلخّصه عنوانها الرئيسي: حضّر السادسة والتاسعة بثقة، من أوّل درس إلى يوم المناظرة. أي أنّها لا تكتفي بالاستعداد في الأسابيع الأخيرة، بل ترافق التلميذ طيلة السنة الدراسية.

أرقام تعكس حجم المحتوى

أوّل ما يلفت الزائر ضخامة المحتوى المتاح. تضمّ المنصّة:

437 درسًا 2792 تمرينًا مصحّحًا 402 ملخّصًا 1416 مصطلحًا في المسارد

ويتوزّع هذا المحتوى على المستويين كما يلي. تضمّ السنة السادسة 214 درسًا و1356 تمرينًا. أمّا السنة التاسعة فتضمّ 223 درسًا و1436 تمرينًا. وهو توزيع متقارب يعكس عناية متساوية بالمرحلتين.

مستويان ومناظرتان وطنيّتان

تفتح المنصّة اليوم بابها لسنتين دراسيتين، وكلّ منهما سنة مناظرة.

السنة السادسة ابتدائي وموادّها الرياضيات والإيقاظ العلمي والعربية والفرنسية والأنقليزية، وتقود إلى مناظرة الدخول إلى المدارس الإعدادية النموذجية.

السنة التاسعة أساسي وموادّها الرياضيات وعلوم الحياة والأرض والعلوم الفيزيائية والعربية والفرنسية والأنقليزية، وتقود إلى امتحان ختم التعليم الأساسي (النوفيام) والتوجيه إلى المعاهد النموذجية.

وتعد المنصّة بفتح سنوات دراسية أخرى قريبًا. ويمكن للزائر أن يترك بريده الإلكتروني ليُعلَم عند توفّر مستوى جديد، من دون أيّ إشهار حسب ما تؤكّده المنصّة.

الدروس: شرح بسيط على وفق البرنامج الرسمي

تُعرض الدروس مرتّبة حسب البرنامج الرسمي لكلّ مادّة. وفي الرياضيات للسنة السادسة، على سبيل المثال، تنقسم الدروس إلى خمس فترات دراسية، فيجد التلميذ ما يدرسه في مدرسته بالترتيب نفسه تقريبًا. وهذا مهمّ لأنّ المنصّة بذلك تكمّل عمل القسم ولا تتعارض معه.

ويقوم كلّ درس على بنية واضحة:

شرح بالأمثلة والرسوم، ليفهم التلميذ الفكرة قبل أن يحفظها. أمثلة محلولة تُظهر طريقة التفكير والحلّ خطوة بخطوة. أخطاء شائعة ينبَّه إليها التلميذ حتى لا يقع فيها يوم الامتحان. اختبار قصير يقيس ما استوعبه فعلًا.

وخانة «الأخطاء الشائعة» جديرة بالتنويه، لأنّ كثيرًا من العلامات الضائعة ليس سببها غياب المعرفة، وإنّما أخطاء متكرّرة يمكن تفاديها متى عُرفت.

التمارين: تصحيح فوري وشرح لموضع الخطأ

هنا تتجلّى قوّة المنصّة. فلكلّ درس سلسلة تمارين تفاعلية في عدّة مستويات من الصعوبة، تُصحَّح فورًا مع الشرح، وتتوفّر منها نسخة PDF للطباعة لمن يفضّل الورق والقلم.

وتصف المنصّة طريقة عملها في ثلاث خطوات:

يحلّ التلميذ التمرين، فيكتب جواب كلّ سؤال كما يفعل في ورقة الامتحان. يُصحَّح فورًا، فإن أخطأ رأى أين أخطأ بالضبط وكيف يصحّح طريقته. يتابع الوليّ التقدّم، فيعرف الدروس المتقنة والدروس التي تحتاج مراجعة ونتائج الامتحانات.

ومن الأمثلة التي تعرضها الصفحة الرئيسية تمرين حسابي بسيط: خيّاطة اشترت قطعة قماش طولها 32 مترًا، واستعملت 3/8 منها للستائر و1/4 للمفارش. فإذا أخطأ التلميذ في حساب الطول الباقي، لا يكتفي النظام بإعلامه أنّ إجابته خاطئة، بل ينبّهه إلى أنّه حسب ما استُعمل بينما السؤال عن الباقي. وهذا هو الفرق بين تصحيح يُعلم بالنتيجة وتصحيح يُعلّم.

الملخّصات والمسارد والقاموس

المراجعة الذكية لا تعني إعادة قراءة الدرس كاملًا في كلّ مرّة. لذلك وفّرت المنصّة 402 ملخّصًا، ملخّصًا لكلّ درس، إضافة إلى مسرد لكلّ مادّة يضمّ المصطلحات الأساسية، ومجموعها 1416 مصطلحًا. وهي أدوات تفيد التلميذ في الأيام التي تسبق الامتحان، حين يحتاج إلى مرور سريع على الأفكار الكبرى.

وتخصّص المنصّة كذلك قاموسًا لكلّ من السنتين السادسة والتاسعة، يساعد التلميذ على فهم المفردات التي قد تعيق فهمه للدروس أو الامتحانات.

امتحانات الثلاثي: اختبار للمكتسبات على امتداد السنة

لا تنتظر المنصّة نهاية السنة لتختبر التلميذ. فهي تضع امتحانات الثلاثي مع الإصلاح بين يديه، وتغطّي في السنة السادسة الرياضيات والإيقاظ العلمي واللغات الثلاث، وفي السنة التاسعة الرياضيات والعلوم والفيزياء واللغات الثلاث.

وتفيد هذه الامتحانات في أمرين: تعوّد التلميذ على أجواء الامتحان وصيغ الأسئلة، وتكشف له مبكّرًا مواطن ضعفه ليعالجها قبل فوات الأوان.

المناظرات التجريبية: التدرّب بالتوقيت وبعدد على 20

من أبرز ما تقدّمه سكولار المناظرات التجريبية. يحلّ فيها التلميذ موضوعًا كاملًا في وقت محدّد، ثمّ يحصل على إصلاح وعدد على 20. وتُظهر الصفحة الرئيسية مثالًا لمناظرة تجريبية حصل فيها التلميذ على 16,5 من 20.

فالمناظرة تُختبر فيها المعارف والقدرة على إدارة الوقت والتحكّم في التوتّر. ولا يتحقّق ذلك إلا بالتدرّب في ظروف قريبة من الظروف الحقيقية، وهذا ما تتيحه المنصّة.

مناظرة السادسة: سباق نحو المدارس الإعدادية النموذجية

تخصّص المنصّة قسمًا كاملًا لمناظرة الدخول إلى المدارس الإعدادية النموذجية، ويحتوي على:

المواضيع الرسمية السابقة 20 موضوعًا نموذجيًا مصحّحًا مناظرات تجريبية بالتوقيت خطّة مراجعة تمتدّ من سبتمبر إلى جوان نصائح للاستعداد

وتعرض المنصّة أرقامًا تبيّن حجم التنافس، استنادًا إلى ندوة صحفية لوزارة التربية بتاريخ 1 جوان 2026: 62 450 مترشّحًا في 2026 لـ3 850 مقعدًا، أي ما يقارب مقعدًا واحدًا لكلّ 16 مترشّحًا. أرقام تفسّر لماذا يحتاج التلميذ إلى استعداد مبكّر ومنظّم لا يُترك للصدفة.

مناظرة التاسعة: النوفيام والمعاهد النموذجية

وفي السنة التاسعة، تغطّي المنصّة امتحان ختم التعليم الأساسي (النوفيام) والتوجيه إلى المعاهد النموذجية. ويضمّ هذا القسم دروس الموادّ الأربع: الرياضيات وعلوم الحياة والأرض والعلوم الفيزيائية والعربية، إضافة إلى المواضيع الرسمية السابقة مع عناصر الإجابة، ومواضيع نموذجية، ومناظرات تفاعلية بالتوقيت.

ومن أرقام دورة 2026 التي تنقلها المنصّة عن وزارة التربية: 25 301 مترشّحًا حاضرًا، ونسبة نجاح بلغت 63,96%، ووُجّه 6 063 تلاميذ إلى المعاهد النموذجية. وهي أرقام تبيّن أنّ النجاح ممكن، لكنّه يتطلّب عملًا منتظمًا.

فضاء الأولياء: خطّة ومتابعة أسبوعًا بأسبوع

يعرف كلّ وليّ أنّ مرافقة الأبناء في الدراسة ليست سهلة، فلا الوقت دائمًا متاح، ولا من السهل معرفة أين يقف الطفل فعلًا. وقد خصّصت سكولار فضاءً للأولياء يقدّم:

خطّة عمل أسبوعية تقترحها المنصّة حسب نتائج الطفل. ويمكن للوليّ إعدادها بنفسه، كما يمكن لتلميذ التاسعة إعدادها بنفسه. تنبيهات عند التراجع أو التأخّر في إنجاز المهامّ. تقريرًا أسبوعيًا بالبريد الإلكتروني. لوحة متابعة لكلّ مادّة، تُظهر نسب التقدّم في الرياضيات والإيقاظ العلمي والعربية وغيرها.

وتعرض الصفحة الرئيسية مثالًا توضيحيًا بيانه للتوضيح فقط، لتلميذ في السنة السادسة يتقدّم جيّدًا بنسبة 82% في الرياضيات و70% في الإيقاظ العلمي و45% في العربية. ويدلّ هذا المثال على الفكرة: أن يعرف الوليّ بنظرة واحدة أين يحتاج طفله إلى دعم إضافي، فيتجنّب الدروس العشوائية ويركّز جهده حيث يلزم.

وللتلميذ بوّابة دخول خاصّة به، وللوليّ والمربّي بوّابة أخرى، بحيث يجد كلّ طرف ما يناسبه. كما تنشر المنصّة قسمًا بعنوان «نصائح للأولياء» يساعدهم على مرافقة أبنائهم.

فضاء المربّي: أدوات للمعلّم والأستاذ

لا تغفل سكولار المربّين. فقد أتاحت لهم فضاءً مجانيًا يمكّنهم من:

إنشاء أقسامهم داخل المنصّة، تكوين سلاسل تمارين وفروض من بنك تمارين سكولار، متابعة نتائج تلاميذهم.

وهذا يوفّر على المعلّم وقتًا كبيرًا في إعداد التمارين وتصحيحها، ويفتح له نافذة على مستوى تلاميذه الفعلي.

الاستعمال دون إنترنت وعلى كلّ الأجهزة

من الإشكالات الواقعية ضعف الاتصال بالإنترنت أو انقطاعه في بعض الأحيان. ولذلك خصّصت المنصّة صفحة لـالاستعمال دون إنترنت. وهي تعمل على الهاتف والحاسوب معًا، ما يجعلها في متناول أغلب الأسر، إذ يكفي هاتف ذكي ليبدأ التلميذ.

مجانية خلال فترة الإطلاق

تعلن المنصّة أنّها مجانية خلال فترة الإطلاق، وتشمل المجانية الدروس والتمارين والامتحانات والمواضيع النموذجية، مع حفظ تقدّم الطفل في حساب مجاني، ومن دون بطاقة بنكية. ويمكن للتلميذ أن يبدأ التعلّم من دون تسجيل، ثمّ ينشئ حسابًا لحفظ نتائجه. وللاطّلاع على التفاصيل المحدّثة، تحيل المنصّة إلى صفحة الاشتراكات.

كيف تستفيد من المنصّة؟ نصائح عملية ابدأ مبكّرًا. خطّة المراجعة تمتدّ من سبتمبر إلى جوان، فلا تنتظر الثلاثي الأخير. اتّبع تسلسل الدروس. يبدأ التلميذ من الدرس ثمّ يتدرّب على تمارينه قبل الانتقال إلى الذي يليه. تعلّم من أخطائك. اقرأ شرح التصحيح بعناية، فهو أهمّ من العدد نفسه. تدرّب بالتوقيت. خصّص حصّة أسبوعية لمناظرة تجريبية في ظروف الامتحان. استعن بالملخّصات في الأيام الأخيرة. هي للمراجعة السريعة لا للتعلّم من الصفر. أشرك الوليّ. يستعمل الوليّ لوحة المتابعة لتوجيه الجهد نحو المواد الأضعف. نظرة إلى المستقبل

تؤكّد سكولار أنّ مستويات أخرى ستُضاف قريبًا، وهو ما يعني أنّ المنصّة تنوي النموّ لتغطّي مراحل أوسع من التعليم الابتدائي والإعدادي. وإلى حين ذلك، يمكن لأولياء التلاميذ في بقيّة المستويات تسجيل بريدهم ليكونوا أوّل من يعلم.

خاتمة

تجمع سكولار Scolaire.tn بين ما يحتاجه التلميذ من دروس وتمارين وامتحانات، وما يحتاجه الوليّ من خطّة ومتابعة، وما يحتاجه المربّي من أدوات تنظيم. وهي تفعل ذلك بالعربية، وعلى وفق البرنامج الرسمي التونسي، وبروح عملية تضع المناظرتين الوطنيّتين نصب عينيها.

وليس في أيّ منصّة رقمية بديلٌ عن جهد التلميذ ودعم أسرته ومعلّميه، لكنّ الأداة الجيّدة تختصر الطريق وتوضّح الرؤية. فمن كان له طفل في السادسة أو التاسعة، فإنّ زيارة المنصّة وتجربة تمرين أو مناظرة تجريبية على https://scolaire.tn/ لا تكلّف شيئًا خلال فترة الإطلاق، وقد تغيّر طريقة استعدادهم للمناظرة.