Telegram RegisterThe public register of Telegram

Channel

Живое обучение

@prolearning

On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry

20,893subscribers

-31 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001183242208
TypeChannel
Username@prolearning
DescriptionКак учатся взрослые? И почему они этого не делают? И как исправить? Отвечает Елена Тихомирова, автор книги "Обучение со смыслом". Курсы tikhomirovaelena.ru Автор @ElenaELC Про сотрудничество и выступления @sol_julia (рекламы нет) #6SKJA
Created11 December 2017measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/prolearning

Growth

20,89320,92420,908.56 August 2026 — 20,924 subscribers6 August 2026 — 20,924 subscribers6 August 2026 — 20,917 subscribers7 August 2026 — 20,912 subscribers8 August 2026 — 20,904 subscribers9 August 2026 — 20,896 subscribers10 August 2026 — 20,901 subscribers11 August 2026 — 20,898 subscribers12 August 2026 — 20,893 subscribers6 August 202612 August 2026
9 measurements spanning 6 days, net -31. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 20,888–20,929 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 12:5720,893-5
11 Aug 2026, 13:4620,898-3
10 Aug 2026, 16:3520,901+5
9 Aug 2026, 17:0120,896-8
8 Aug 2026, 15:4520,904-8
7 Aug 2026, 15:1620,912-5
6 Aug 2026, 12:5120,917-7
6 Aug 2026, 04:1520,924no change
6 Aug 2026, 04:0720,924first reading

Engagement

21 posts held, back to 8 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
7.86%
avg views ÷ 20,893 subscribers
Avg views / post
1,640
8 posts measured
Reaction rate
2.44%
reactions ÷ views · ER floor
Posts in window
8
of 21 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 August 2026
Posts held21 (8 June 202610 August 2026)
Views total13,139
Reactions total320
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 23:17 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
285
Videos
9
Links
915

Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

998 reactions across 21 posts, in 6 distinct kinds. The most used accounts for 50.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
50350.4%
🔥28228.3%
👍16316.3%
custom 5449369464812369727383.81%
70.701%
custom 544941128061396114250.501%

Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 21 of the 21 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 998reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 21 most recent posts we hold, published 8 June 2026 to 10 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Telegram Stars

Stars received
1
across the posts below
Posts paid on
1
of 21 we hold a reading for · 5%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @prolearning. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 21 most recent posts we hold for this entry, published 8 June 2026 to 10 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

10 Aug 2026, 04:02 UTC819 views38 reactionsread 12 August 2026
Photo

Мифы про обучение взрослых Писала тут для книги главные мифы про обучение взрослых (правда, похоже, в книгу это в итоге не войдет). Собрала короткую инфографику для вас с моими самыми любимыми. ____ Живое обучение живет еще в Максе и в ВК.

🔥2216

6 Aug 2026, 04:00 UTC≈1,300 views30 reactionsread 12 August 2026
Photo

Сознание новичка Вот с этой темой я очень долго боролась в книге, никак не могла найти ей правильное место - в самом начале или в третьей, заключительной части. Сейчас нашла, но пока не скажу где. Зато есть инфографика про то, что такое сознание новичка и как его тренировать ____ Живое обучение живет еще в Максе и в ВК.

16🔥13custom 54493694648123697271

3 Aug 2026, 04:01 UTC≈1,610 views36 reactionsread 12 August 2026
Photo

Инфографика про мотивацию взрослых Оригинальный текст про это вот тут. ____ Живое обучение живет еще в Максе и в ВК.

22👍8🔥6

30 Jul 2026, 04:03 UTC≈1,970 views28 reactionsread 12 August 2026
Photo

Что мешает учиться прямо сейчас? Чуть ли не главная идея моей книги - идеальных условий не будет, учиться нужно сейчас. В тему - небольшая инфографика ____ Живое обучение живет еще в Максе и в ВК.

23custom 54493694648123697275

27 Jul 2026, 04:05 UTC≈1,960 views45 reactionsread 12 August 2026

Ловушки проектирования Сборник ошибок, которые часто приводят нас не туда Ко мне регулярно приходят чужие проекты на аудит. И почти всегда я вижу не уникальные ошибки, а одни и те же ловушки, в которые когда-то попадала сама. В этом тексте - сборник таких ловушек, про которые я писала последние несколько лет. Ловушка первая, самая частая: мы принимаем передачу информации за обучение. Кажется, что чем больше материа

👍2416🔥5

23 Jul 2026, 04:01 UTC≈1,750 views33 reactionsread 12 August 2026

Право на ошибку Тексты о том, как страх ошибиться мешает учиться Я долго была уверена, что перфекционизм это скорее хорошо. Что именно неуёмное желание быть лучшей и толкает меня учиться, и даже ругала себя за то, что иногда соглашаюсь на «и так нормально». Я сильно ошибалась, и за пару лет написала об этом несколько текстов. Собрала их вместе. Начну с главного. В «Перфекционизм против обучения» я разобралась, что

🔥2211

20 Jul 2026, 04:00 UTC≈1,770 views60 reactions1 Starread 12 August 2026

Про наше внимание Несколько текстов, сведённых в один Пока я писала книгу, я поймала себя на том, что сложнее всего не писать, а фокусироваться. Села работать, отвлеклась на уведомление о погоде, а очнулась где-то между видео про обрезку помидоров и страницей набора на курс. Снова и снова я понимаю, что внимание - это самый ценный ресурс, который у нас. Начну с неприятного. Внимание давно перестало быть нашим свобо

🔥36👍1110custom 54494112806139611423

16 Jul 2026, 04:08 UTC≈1,960 views50 reactionsread 12 August 2026

Как учится тот, кто учит других Несколько лет честных наблюдений за собой как за ученицей Меня постоянно спрашивают, как я сама учусь. Первый раз вопрос прилетел из зала на одном выступлении, и с тех пор повторяется на каждом втором интервью. Под работу над книгой про обучение взрослых был повод пособирать мои посты на эту тему. Начну со слегка неловкого. После первого вуза я не училась формально почти ни дня. На к

31👍11🔥8

13 Jul 2026, 04:01 UTC≈2,080 views86 reactionsread 12 August 2026

Привычка к дискомфорту Текст о том, что идеальных условий не будет В нашем мире все постоянно стремится к комфорту. Если посмотреть на рекламу, то продают нам чаще всего именно удобство и комфорт. От чайника для квартиры. И часто просачивается идея, что если вы найдете то занятие, которое вам нравится и в котором будет ваш большой смысл, то вы ни дня не будете работать, вы будете только заниматься любимым делом. Я

59🔥14👍13

9 Jul 2026, 04:04 UTC≈2,200 views48 reactionsread 12 August 2026

Как я училась отдыхать Подборка о том, как учиться тому, чему вроде бы учиться не нужно Раз уж я ушла в писательскую тишину, одну из подборок точно стоит посвятить этой теме. За пару лет я написала про отдых, силы и тишину не мало, теперь попробую все собрать в одном тексте. Начну с признания, которое далось мне тяжелее всего. Первые пятнадцать лет работы я провела в неизменно уставшем состоянии и почти никому об э

442🔥2

6 Jul 2026, 04:01 UTC≈2,400 views56 reactionsread 12 August 2026

Книги на лето Подборка книг о том, что нас никто научить не может Я пишу о том, как учиться взрослому. И стол мой завален книгами: с какими-то спорю, на какие-то ссылаюсь. Собрала для вас подборку на тему личного обучения, мне кажется, что лето для этого - отличное время. 📖 Питер Браун, Генри Рёдигер, Марк Макдэниел, «Запомнить всё» (Альпина). О том, что самые привычные способы (перечитывание, зубрёжка) почти не ра

35🔥201

2 Jul 2026, 04:01 UTC≈2,290 views61 reactionsread 12 August 2026

Списывание Текст о том, что нужно слушать, слышать и записывать Недавно была на одном онлайн мероприятии. Что-то вроде обучающей конференции про поиск смысла в том, что ты делаешь. Очень понравилась режиссура события: ведущий, приглашенные спикеры в разных форматах: интервью, выступление, короткие вставки. Много чего для себя вытащила для будущих событий. Но зацепило меня больше всего другое. Ведущим конференции бы

🔥3328

Showing the 12 most recent of 21 posts we hold for @prolearning. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Citation-graph rank

Citation-graph rank — 110,790 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 10 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Живое обучение” (@prolearning), 20,893 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/prolearning.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.