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Channel

Лаборатория онлайн-обучения

@educational_lab

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

9,200subscribers

-60 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
Created9 November 2021 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live18 September 2026
Measurements held13
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/educational_lab

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 50% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

9,1999,2609,229.56 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 subscribers22 August 2026 — 9,225 subscribers26 August 2026 — 9,220 subscribers29 August 2026 — 9,216 subscribers4 September 2026 — 9,218 subscribers10 September 2026 — 9,210 subscribers13 September 2026 — 9,199 subscribers18 September 2026 — 9,200 subscribers9,2006 August 202618 September 2026
13 measurements spanning 43 days, net -60. 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 9,190–9,269 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
18 Sept 2026, 11:389,200+1
13 Sept 2026, 21:579,199-11
10 Sept 2026, 13:369,210-8
4 Sept 2026, 23:409,218+2
29 Aug 2026, 16:559,216-4
26 Aug 2026, 10:029,220-5
22 Aug 2026, 23:449,225+2
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

41 posts held, back to 8 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 33 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.66%
avg views ÷ 9,200 subscribers
Avg views / post
245
2 posts measured
Reaction rate
2.86%
reactions ÷ views · ER floor
Posts in window
2
of 41 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 28 August 2026
Posts held41 (8 July 2026 – 28 August 2026)
Views total490
Reactions total14
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 11:31 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

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

362 reactions across 38 posts, in 6 distinct kinds. The most used accounts for 34.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤12534.5%
👍10829.8%
🔥8423.2%
💯369.94%
🏆61.66%
🤓30.829%

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 41 of the 41 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 388 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 41 most recent posts we hold, published 8 July 2026 to 28 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
2.44%
1 of 41 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
631
over 1 measured post
Median views · rest
663
over 40 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 41 most recent posts we hold, published 8 July 2026 to 28 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

28 Aug 2026, 14:22 UTC214 views7 reactionsread 29 August 2026
Photo

Пятница. Вечер. Листаю свежие исследования. Обновляю инструкции (промты) для нейросетки по созданию тестовых заданий. Пока эффективное формулирование дистракторов — самая сложная задачка. Сколько не меняю или дополняю инструкции, а ошибки возникают.

🔥5👍1🤓1

28 Aug 2026, 08:39 UTC276 views7 reactionsread 29 August 2026
Photo

Ищу нестандартные функции генеративных нейросетей в своей работе. Открыл для себя очень полезную функцию при работе с документами в ChatGPT. Делюсь с вами находкой. Если документ был заметно доработан или появилась его новая редакция, нейросеть может отметить комментариями, что именно изменилось по сравнению с предыдущей версией. Например, кратко пояснить, какой раздел переработан и почему (причём на основании ком…

❤6👍1

27 Aug 2026, 06:52 UTC237 views3 reactionsread 29 August 2026
Forwarded from @lab_vacancies

Зачем вузу карьерные центры, если работодатели используют ИИ? В последнее время я всё чаще наблюдаю, как при вузах открываются новые карьерные центры. Это видно в том числе по количеству вакансий. По моим наблюдениям, за последний год их стало примерно на 10–15% больше. Но дело в том, что работодатели постепенно встраивают искусственный интеллект в подбор сотрудников, а последствия этого процесса для карьерных цент…

💯2👍1

26 Aug 2026, 07:01 UTC326 views7 reactionsread 29 August 2026
Photo

Почему удобство платформы особенно важно после запуска курса Я всегда ценил обучающихся, которые дают содержательную обратную связь по нашим образовательным продуктам. Например, сейчас на курсе «Управления образовательными проектами: основы» есть несколько участников, которые по мере прохождения программы присылают свои предложения. Причём обратная связь действительно предметная. К подобным правкам я отношусь спо…

🔥7

25 Aug 2026, 04:39 UTC≈1,030 views5 reactionsread 29 August 2026

Карьерное развитие через профессиональные задачи Друзья, продолжаем рубрику «Персональная траектория и карьерный разворот: как собрать свой рост перед новым сезоном». Первый материал рубрики вы можете изучить здесь, второй — здесь, третий — здесь В последнее время работаю над проектами, связанными с внедрением инноваций в образовательную методологию с позиции подходов, моделей и т.д. И недавно обнаружил зону для п…

❤3👍2

24 Aug 2026, 08:10 UTC368 views5 reactionsread 29 August 2026
Photo

ИИ в вузах — это вопрос институциональной трансформации 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 последнее время мне удалось довольно глубоко изучить то, как университеты используют искусс…

👍3🔥2

23 Aug 2026, 15:59 UTC437 views15 reactionsread 29 August 2026

В последнее время мне всё чаще кажется, что мы немного запутались в том, что действительно является для нас ценным. Запутались в суете бытовых дел, в рабочей повседневности, в бесконечном потоке задач, сообщений, встреч. Будто мы постепенно привыкаем оценивать жизнь через эффективность, скорость, результативность, количество выполненной работы. И всё реже задаём себе вопросы о человеческих качествах. Быть может се…

👍7❤3💯3🔥2

21 Aug 2026, 04:39 UTC584 views16 reactionsread 29 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 😀

👍7❤6🔥3

20 Aug 2026, 12:04 UTC567 views16 reactionsread 29 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…

🔥8❤5👍3

19 Aug 2026, 07:03 UTC631 views10 reactionsread 29 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🔥3👍2🏆1

18 Aug 2026, 04:39 UTC≈1,240 views5 reactionsread 29 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👍2

17 Aug 2026, 09:59 UTC580 views14 reactionsread 29 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…

👍7❤5🔥2

Showing the 12 most recent of 41 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 2 posts 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
25 August 2026

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.

Живое обучение
@prolearning · 20,688
Telegram ranks this channel #1 of 100 here — alongside 99 others — read 26 September 2026
Теории и Практики
@tandp_ru · 22,235
Telegram ranks this channel #6 of 100 here — alongside 99 others — read 21 September 2026
Эдтехно | образование
@edtexno · 21,287
Telegram ranks this channel #9 of 99 here — alongside 98 others — read 24 September 2026
Школа мышления. Вояж в страну загадок.
@shkolamishleniA · 22,743
Telegram ranks this channel #9 of 97 here — alongside 96 others — read 20 September 2026
ОбОбраз
@ob_obraz · 30,398
Telegram ranks this channel #9 of 100 here — alongside 99 others — read 7 September 2026
Образование, которое мы заслужили
@ru_education · 42,533
Telegram ranks this channel #10 of 98 here — alongside 97 others — read 29 August 2026
Вакансии в образовании
@edujobs · 65,872
Telegram ranks this channel #12 of 99 here — alongside 98 others — read 21 August 2026
факультет
@studyfaculty · 43,981
Telegram ranks this channel #13 of 97 here — alongside 96 others — read 5 September 2026
ChatGPT, помоги!
@GPThelp_ru · 509,707
Telegram ranks this channel #15 of 91 here — alongside 90 others — read 10 August 2026
Ффринг | Вайбкодинг
@aiffring · 22,006
Telegram ranks this channel #20 of 88 here — alongside 87 others — read 23 September 2026
AI и точка.
@ai4telegram · 922,526
Telegram ranks this channel #31 of 73 here — alongside 72 others — read 8 August 2026
Вакансии для своих✨
@cozy_hr · 52,299
Telegram ranks this channel #36 of 100 here — alongside 99 others — read 25 August 2026
Нетология
@netology_ru · 27,487
Telegram ranks this channel #43 of 96 here — alongside 95 others — read 10 September 2026
Skillbox: образовательная платформа
@skillboxru · 36,669
Telegram ranks this channel #43 of 97 here — alongside 96 others — read 3 September 2026
СберУниверситет
@sber_university · 24,091
Telegram ranks this channel #47 of 100 here — alongside 99 others — read 17 September 2026
Наука и университеты
@naukauniver · 43,122
Telegram ranks this channel #52 of 97 here — alongside 96 others — read 28 August 2026
RazoomJobs | Вакансии – EdTech, International
@razoomjobs · 26,712
Telegram ranks this channel #54 of 98 here — alongside 97 others — read 12 September 2026
Актион Образование
@action_obrazovanie · 37,106
Telegram ranks this channel #66 of 95 here — alongside 94 others — read 1 September 2026

This channel appears in 18 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“Лаборатория онлайн-обучения” (@educational_lab), 9,200 subscribers as measured 18 September 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.