Education — 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 13 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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 the other topics.
Growth
25 measurements spanning 90 days, net +280. 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 5,471–5,988 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)
Subscribers
Change
6 Nov 2026, 06:17
5,877
-19
2 Nov 2026, 20:29
5,896
-32
30 Oct 2026, 12:46
5,928
+344
27 Oct 2026, 17:44
5,584
+7
25 Oct 2026, 01:19
5,577
+7
22 Oct 2026, 07:06
5,570
+33
18 Oct 2026, 16:46
5,537
+1
15 Oct 2026, 17:28
5,536
-7
12 Oct 2026, 22:27
5,543
-20
6 Oct 2026, 15:42
5,563
-17
29 Sept 2026, 17:01
5,580
+49
19 Sept 2026, 15:22
5,531
-4
14 Sept 2026, 17:57
5,535
-13
11 Sept 2026, 10:39
5,548
-8
6 Sept 2026, 12:16
5,556
-9
1 Sept 2026, 18:05
5,565
-4
29 Aug 2026, 22:13
5,569
-9
26 Aug 2026, 21:32
5,578
-8
23 Aug 2026, 21:18
5,586
+8
20 Aug 2026, 09:46
5,578
first reading
Engagement
11 posts held, back to 5 August 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 8 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
10.2%
avg views ÷ 5,877 subscribers
Avg views / post
599
3 posts measured
Reaction rate
3.51%
reactions ÷ views · ER floor
Posts in window
4
of 11 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
Window
Rolling 30 days · latest post in window 4 November 2026
Posts held
11 (5 August 2026 – 4 November 2026)
Views total
1,796
Reactions total
63
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 02:12 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
21s
Average length
11s
Measured directly from 2 videos 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
183 reactions across 10 posts, in 5 distinct kinds. The most used accounts for 75.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
138
75.4%
🔥
25
13.7%
❤🔥
17
9.29%
😍
2
1.09%
⚡
1
0.546%
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 10 of the 11 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 183 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 5 August 2026 to 4 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 1 of 4 posts held from the last 30 days (25.0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Можно ли написать почти чёрную ночь, не используя чёрную краску?🩶
Анна Завьялова уверена, что можно — именно так рождаются самые живые и атмосферные тени.
В своих работах Анна практически не использует чёрный: он может сделать тень плоской, «погасить» пространство и не оставить в нём места для света и воздуха. Вместо этого художница собирает тёмное из нескольких оттенков.
Подробнее о любимых смесях Анны и пейзажных…
Вдохновение чёрным: почему чёрно-белая графика такая выразительная? 🖤
— мы попросили ответить на этот вопрос нашего лектора-графика, Агееву Анастасию:
Для меня чёрный инструмент и белый лист — как своеобразная перезагрузка. Из работы уходит цветовой шум, и я остаюсь один на один с линией, пятном и штрихом 😍
Без цвета особенно хорошо становится видно всё самое главное:
— силуэт собирает изображение
— линия показывае…
1⃣курс = 2⃣ курса: весь ноябрь у нас своя математика
...потому, что со 2 по 30 ноября — "Чёрная пятница" в Marker School. В этом году особенно приятные условия будут действовать ЦЕЛЫЙ МЕСЯЦ!
🎊 "Чёрная пятница" в Marker School — это:
1. Самые большие скидки в году (до 60%) на курсы и сборники
2. Доступ к купленным курсам навсегда
3. +1 курс в подарок*
*покупая курс в период с 2 по 30 ноября, вы получаете ещё один ку…
НОВЫЙ ТЕСТ-ДРАЙВ УЖЕ ОТКРЫТ: ПРО-курс архитектурного скетчинга 😍
Открываем целый блок курса Екатерины Пластининой!
Этот курс — почти живая энциклопедия архитектуры
«ПРО-курс архитектурного скетчинга» — один из самых масштабных курсов Екатерины Пластининой. На курсе вы будете разбирать, как менялись здания в разные эпохи: какие появлялись формы, силуэты, окна, арки, крыши, орнаменты, пропорции и детали.
Екатерина с…
Собрали отзывы учеников на курсы Екатерины Пластининой.
Спасибо за ваши тёплые слова 💛
Нам очень важно видеть, что после обучения на курсе сложная тема становится понятной, перспектива строится проще и грамотнее, а архитектурные сюжеты больше не пугают.
Сейчас на курсы Екатерины — СКИДКИ до 40%,
а на сборники курсов — СКИДКИ до 50%.
Выбирайте свой удобный и выгодной сборник по городскому скетчингу: https://marker.…
Екатерина Пластинина — большой любитель пленэров 😋
"Каждый пленэр — уникальный и запоминающийся. Мне особенно нравится выбирать для себя красивые места в разных городах. Но я предпочитаю не просто сидеть на улице и рисовать. Я люблю сочетать приятное с полезным 😆
Лучше всего — рисовать, сидя в уютном кафе: с комфортом и вдохновением. Здорово, если получается снять жильё с прекрасным видом из окон, чтобы можно было …
Рисуем с Екатериной Пластининой: Транспорт в городе
Транспорт в городском скетчинге — тема "со звёздочкой" 😅
Машины кажутся слишком сложными. Колёса уезжают не туда.
Скутеры, велосипеды, трамваи, лодки... вроде бы делают город живым, но как только нужно их нарисовать, сразу хочется поставить на это место дерево.
Знакомо?
- Тогда рекомендуем пройти бесплатный тест-драйв курса Екатерины Пластининой Транспорт в городе…
Что делать и НЕ делать при наброске линером?
Совет от Екатерины Пластининой:
❌ Не начинайте с карандаша и долгих терзаний, как приступить, тут же применяя "магию ластика".
✅️ Рисуйте сразу линером: лучше тонким (0,1), не выжимая из него все 0,5. Скользите им, чуть касаясь бумаги, оправдывая суть слова "набросок".
❌️ Не используйте перекрёстную штриховку (это привилегия карандашных рисунков). Штриховка "наискосок"…
У Екатерины Пластининой 7 больших курсов по городскому скетчингу в Marker School✨
...и мы сделали из них 5 выгодных сборников с разными акцентами:
— "база" городского скетчинга
— архитектурный скетчинг
— графика и монохром
— сложные городские сюжеты
— транспорт, детали и атмосфера города
Сейчас на сборники — максимальные СКИДКИ:
сборник из 2-х курсов: —40%
сборник из 3-х курсов: —45%
сборник из 4-х курсов: —50%
…
Городские недели с Екатериной Пластининой: Bella Grafica! Архитектурный скетчинг
Давно хотели разобраться с архитектурой, перспективой и городскими деталями? Отличный момент попробовать!
✅ В БЕСПЛАТНОМ тест-драйве открыт урок №11:
«Перспектива с одной точкой схода: арки, двери и окна»
https://marker.school/courses/gorodskaya-grafika#testdrivelessons
Это одна из тех тем, после которых городские сюжеты становятся по…
❤15❤🔥3⚡1
Showing the 11 most recent of 11 posts we hold for @markerschoolmk. 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.
Mentions
Named by 2 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.
Named by
Channels on the register whose posts name this channel's handle.
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.
Художник Онлайн @hudozhnik_online · 18,797 Telegram ranks this channel #8 of 89 here — alongside 88 others — read 5 October 2026
KalachevaSchool @kalachevaSchool · 22,228 Telegram ranks this channel #16 of 92 here — alongside 91 others — read 22 September 2026
Школа Рисования Всем Арт @vsemartschool · 20,203 Telegram ranks this channel #28 of 91 here — alongside 90 others — read 28 September 2026
SKETCHBOOK | СКЕТЧБУК @your_sketchbook · 19,859 Telegram ranks this channel #43 of 93 here — alongside 92 others — read 29 September 2026
Собака-рисовака @sobaka_risovaka · 32,864 Telegram ranks this channel #50 of 90 here — alongside 89 others — read 4 September 2026
АНТИПИН.АРТ @antipinart · 31,904 Telegram ranks this channel #59 of 88 here — alongside 87 others — read 5 September 2026
Красный Карандаш @krasniy_karandash · 28,223 Telegram ranks this channel #68 of 86 here — alongside 85 others — read 9 September 2026
This channel appears in 7 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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“Мастер-классы Marker School” (@markerschoolmk), 5,877 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/markerschoolmk.
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.