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Channel

Лаборатория онлайн-обучения

@educational_lab

On this record: Growth · Engagement · What this channel posts · Reactions · Advertising · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry

9,223subscribers

-37 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001570239866
TypeChannel
Username@educational_lab
DescriptionКанал полезен для всех, кто связан с проектированием образовательных продуктов. Автор @osipov_education Сайт автора osipov-education.ru По сотрудничеству @darya_egrv Чат @osipov_education_lab РКН: https://www.gosuslugi.ru/snet/675c274f2d90d3244c9fffcb
Created9 November 2021measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live19 August 2026
Measurements held6
Confirmed unchanged1 time, most recently 19 August 2026
On Telegramt.me/educational_lab

Growth

9,2219,2609,240.56 August 2026 — 9,260 subscribers6 August 2026 — 9,260 subscribers9 August 2026 — 9,254 subscribers13 August 2026 — 9,235 subscribers16 August 2026 — 9,221 subscribers19 August 2026 — 9,223 subscribers9,2236 August 202619 August 2026
6 measurements spanning 13 days, net -37. 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 9,215–9,266 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
19 Aug 2026, 13:429,223+2
16 Aug 2026, 14:549,221-14
13 Aug 2026, 03:349,235-19
9 Aug 2026, 21:319,254-6
6 Aug 2026, 02:519,260no change
6 Aug 2026, 01:499,260first reading

Engagement

34 posts held, back to 8 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 23 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
7.86%
avg views ÷ 9,223 subscribers
Avg views / post
725
23 posts measured
Reaction rate
1.27%
reactions ÷ views · ER floor
Posts in window
23
of 34 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 21 August 2026
Posts held34 (8 July 202621 August 2026)
Views total16,676
Reactions total211
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken22 Aug 2026, 18:00 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
518
Videos
78
Links
914

Lifetime counters from Telegram’s own channel header, read 22 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.

Video runtime
3m 57s
Average length
3m 57s

Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

296 reactions across 31 posts, in 6 distinct kinds. The most used accounts for 36.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
10936.8%
👍8629.1%
🔥6321.3%
💯3010.1%
🏆62.03%
🤓20.676%

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 34 of the 34 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 322reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 34 most recent posts we hold, published 8 July 2026 to 21 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.

Advertising

Ad load
2.94%
1 of 34 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
462
over 1 measured post
Median views · rest
725
over 33 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor.A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2Vtzqwqtegb119 August 202619 August 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 34 most recent posts we hold, published 8 July 2026 to 21 August 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

21 Aug 2026, 04:39 UTC294 views12 reactionsread 22 August 2026
Photo

У меня появились новые коллеги в команде. И они уже не просто отвечают на вопросы, а заходят в материалы, анализируют контекст, оставляют комментарии. Причём каждый такой коллега со своей ролью, задачами, ограничениями и т.д. Кажется, скоро попросят перенести задачу по срокам 😀

5👍5🔥2

20 Aug 2026, 12:04 UTC316 views14 reactionsread 22 August 2026

Почему обучающийся пишет «всё понятно», но в итоге ничего не делает? Недавно разбирал один учебный курс. Двенадцать модулей, сильный эксперт, удобная с точки зрения UX/UI платформа. По обратной связи от обучающихся всё вроде хорошо. При этом до конца курса доходили только 3 из 10, а задания выполняли ещё меньше. Я задал автору один вопрос: «Какую конкретную задачу обучающийся научится решать после прохождения курс

🔥84👍2

19 Aug 2026, 07:03 UTC462 views9 reactionsread 22 August 2026
Advertisementerid 2Vtzqwqtegb

Третий год подряд наблюдаю за образовательными проектами, которые номинируются на премию Digital Learning. В этом году снова вошел в состав жюри. За это время у меня сформировалось одно устойчивое наблюдение: известность проекта на рынке корпоративного обучения и его качество далеко не всегда связаны между собой. Каждый год среди заявок встречаются проекты, о которых профессиональное сообщество пока почти не знает.

4👍2🔥2🏆1

18 Aug 2026, 04:39 UTC≈1,020 views4 reactionsread 22 August 2026

Почему внутренний рынок талантов может стать новым приоритетом для HR? Друзья, продолжаем рубрику «Персональная траектория и карьерный разворот: как собрать свой рост перед новым сезоном». Первый материал рубрики вы можете изучить здесь, второй — здесь Я периодически наблюдаю за дискуссиями работодателей и HR-специалистов и в последнее время всё чаще замечаю одно смещение. Вопрос о том, где найти нового сотрудник

3👍1

17 Aug 2026, 09:59 UTC459 views12 reactionsread 22 August 2026

Когда сфера EdTech проходит непростой период и я сам сталкиваюсь с определёнными трудностями, особенно интересно встречаться с людьми, разговаривать с ними, узнавать, как они смотрят на работу в целом и проекты. Недавно встретился с хорошим знакомым, у которого в своё время многому научился в плане продуктового и, я бы даже сказал, предпринимательского мышления. В разговоре он сказал, что заработок никогда не был д

👍64🔥2

16 Aug 2026, 13:59 UTC449 views13 reactionsread 22 August 2026

Насколько важно практику, доказана образовательная модель или нет? На этой неделе в чате канала возник интересный разговор о научной обоснованности различных образовательных моделей и подходов. И в ходе дискуссии я понял, что важно развести две характеристики, которые довольно часто смешиваются: «работает на практике» и «научно обосновано». Возьмём ту же таксономию Блума. Я бы не говорил, что она вообще не имеет

8👍3💯2

14 Aug 2026, 04:39 UTC522 views8 reactionsread 22 August 2026
Photo

Вижу, что многие из вас начали пользоваться правильной стратегией 😀 все авторские образовательные продукты, фреймворки и т.д. находятся 👉🏼 здесь (достаточно просто выбрать нужный вам раздел во вкладке «обучение»)

6👍2

13 Aug 2026, 11:59 UTC593 views9 reactionsread 22 August 2026
Photo

Если после обучения выросли бизнес-показатели, можем ли мы считать курс эффективным? Сотрудники прошли обучение, затем увеличилась их производительность. Вроде всё очевидно. Но научной с точки зрения между этими двумя событиями может находиться множество других факторов. Поэтому при оценке корпоративного обучения возникает важный методологический вопрос: что именно в действительности можно приписать учебному курсу

👍9

12 Aug 2026, 07:59 UTC539 views9 reactionsread 22 August 2026

А кто сегодня задаёт направление развития образования? Продолжаем нашу рубрику про трансформацию образования. Данная рубрика посвящена тому, каким я вижу изменения образовательной системы на разных её уровнях. По хэштегу #ТрансформацияОбразования вы можете посмотреть материалы, которые уже выходили на канале на эту тему. В прошлом месяце вышел комментарий Алексея Владимировича Савватеева к заявлению Германа Оскаро

💯4👍32

11 Aug 2026, 04:40 UTC≈1,300 views5 reactionsread 22 August 2026

Как строить карьеру, если непонятно, где junior, middle и senior? Друзья, продолжаем рубрику «Персональная траектория и карьерный разворот: как собрать свой рост перед новым сезоном». Первый материал рубрики вы можете изучить здесь Недавно мы с коллегой проводили на канале «Лаборатории вакансий в образовании» исследование, в котором изучали проблемы, с которыми сталкиваются соискатели в сфере корпоративного обучен

2🔥2👍1

10 Aug 2026, 09:50 UTC568 views6 reactionsread 22 August 2026

Можно ли проектировать образование с ИИ без системной модели? Сегодня в чате «Лаборатории онлайн-обучения» получилась большая дискуссия, которая началась с разговора об ИИ, а закончилась вопросом о том, как вообще должно производиться новое знание об образовании. Попробую собрать основные позиции участников в одну линию рассуждения. Евгений начал с довольно фундаментального наблюдения о том, что образование постоя

2👍2🔥2

9 Aug 2026, 17:20 UTC505 views8 reactionsread 22 August 2026

Сегодняшнее осмысление проблем системы образования в условиях развития генеративного искусственного интеллекта, пожалуй, требует изменения самой постановки задачи. Иными словами, необходимо переосмыслить вопрос о том, чему и зачем должна учить современная система образования. В качестве исторического примера подобного эвристического хода можно вспомнить британского математика Алана Тьюринга. В своей работе Computin

👍6🔥2

Showing the 12 most recent of 34 posts we hold for @educational_lab. 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.

Posts edited after publishing

@educational_lab edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
19 August 2026
Most recent edit
19 August 2026

Citation-graph rank

Citation-graph rank — 48,710 of 1,583,249entries 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

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 5 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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Вакансии в образовании
@edujobs · 65,494
Telegram ranks this channel #12 of 99 here — alongside 98 others — read 21 August 2026
ChatGPT, помоги!
@GPThelp_ru · 479,942
Telegram ranks this channel #15 of 91 here — alongside 90 others — read 10 August 2026
AI и точка.
@ai4telegram · 872,570
Telegram ranks this channel #31 of 73 here — alongside 72 others — read 8 August 2026

This channel appears in 3 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 19 August 2026 — this entry's latest reading, not the date you are reading this.

“Лаборатория онлайн-обучения” (@educational_lab), 9,223 subscribers as measured 19 August 2026. Telegram Register, tgregister.com/channel/educational_lab.

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.