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Channel

Екатерина Ведяшкина | Нейросети и EdTech

@katerinaEAV_AI_EdTech

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

2,820subscribers

+0 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1003462825467
TypeChannel
Username@katerinaEAV_AI_EdTech
DescriptionЗаставь нейросети делать твою работу. Инструменты и промпты, чтобы: 🛠 Ускорить процессы в 2-3 раза 🚀 Делегировать рутину AI 🧠 Внедрить решения из реальной практики Твоя шпаргалка от PO Zerocoder. @Vediashkina_Katerina
CreatedBetween 1 November 2025 and 31 March 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live14 August 2026
Measurements held2
On Telegramt.me/katerinaEAV_AI_EdTech

Growth

2,8207 Aug 2026, 19:25 — 2,820 subscribers7 Aug 2026, 20:02 — 2,820 subscribers7 Aug 2026, 19:257 Aug 2026, 20:02
2 measurements taken within a single day. 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 2,817–2,823 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
7 Aug 2026, 20:022,820no change
7 Aug 2026, 19:252,820first reading

Engagement

20 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
21.4%
avg views ÷ 2,820 subscribers
Avg views / post
603
3 posts measured
Reaction rate
1.94%
reactions ÷ views · ER floor
Posts in window
3
of 20 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 29 July 2026
Posts held20 (8 June 202629 July 2026)
Views total1,808
Reactions total35
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 20:02 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
23
Videos
4
Links
23

Lifetime counters from Telegram’s own channel header, read 7 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

243 reactions across 17 posts, in 13 distinct kinds. The most used accounts for 32.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍7832.1%
🔥6426.3%
5623.0%
😁135.35%
🤣114.53%
52.06%
🤨52.06%
💯41.65%
🍾20.823%
👏20.823%
custom 536184781525537287110.412%
👎10.412%
😱10.412%

Custom emoji. One row above is a 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 count beside it isTelegram’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 17 of the 20 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 243reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 8 June 2026 to 29 July 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

29 Jul 2026, 07:45 UTC421 views9 reactionsread 7 August 2026

Иду к вам поделиться происходящим 🚶‍♂️ А еще надеюсь, может быть, вы (исходя из личного опыта) сможете помочь мне найти правильные вопросы) Внимание: дальше будет абракадабра, если есть время гуглить и изучать, то буду рада вашим идеям. Если нет, то считайте, что я просто бессвязно пытаюсь объяснить то, в чем сама плаваю пока что. Но вдруг вы понимаете о чем я 🙏 Я разобралась с перечнем операций (действий), котор

🤨52👍1👏1

22 Jul 2026, 09:58 UTC645 views12 reactionsread 7 August 2026

Вести с полей 📖 — Gemini отупел в край 😭 — ChatGPT слишком много болтает( — Алиса ПРО дает хорошие идеи и качественно верифицирует ответ, но задачу выполняет плохо 🦕 — Сloud - жадина, бесплатных запросов не хватает, чтобы понять адекватный ли он в принципе. Текста много, пользы не получила в текущей задаче 😶 — Сomet (а в нем и Перплексити) - работает от случая к случаю. В бесплатной версии не дает выбирать модель и

55🔥2

19 Jul 2026, 05:28 UTC742 views14 reactionsread 7 August 2026

😁😁😁 https://youtube.com/shorts/GGduXOVfyU8?si=v83PtPUlH4trHQDK

🤣11😁3

15 Jul 2026, 14:03 UTC911 views16 reactionsread 7 August 2026

Один день в 2200 году 🤩 Делюсь с вами видео, которое с помощью ИИ сделал мой 13-тилетний сын) https://youtube.com/shorts/vqH0IDW4lPg?si=0M6NKUxOm_-BKBp Все как мы учили на курсах, которые я создавала: - Сгенерировал идеи, сценарий и промпты для изображений и для видео - Сгенерировал изображения и проследил, чтобы персонажи на разных кадрах были одними и теми же - Сгенерировал видеофрагменты Монтаж делал в ручную,

👍9🔥6👏1

15 Jul 2026, 07:44 UTC839 views11 reactionsread 7 August 2026

Обожаю, когда нейросеть сначала сама делает ошибку, ничего не получается и нужно долго спрашивать, почему и зачем делать именно так. И нейронка такая: "Да, ты права, это так не работает" 😶 Что вы делаете в таких ситуациях?)

😁101

10 Jul 2026, 06:44 UTC≈1,050 views17 reactionsread 7 August 2026

Лучший промпт для работы с новыми интерфейсами 👩🏼‍💻 При работе с новой программой или сервисом очень важно, чтобы нейросеть не болтала лишнего и не отвлекала. Для этого использую вот такой промпт (кто-то из вас уже забирал его в личку): Ты — пошаговый технический инструктор и ментор. Твоя задача — обучить меня настройке программы, которую я укажу ниже. Правила: ЭКОНОМИЯ КОНТЕКСТА: Пиши максимально коротко. Убирай

13👍4

8 Jul 2026, 10:11 UTC770 views8 reactionsread 7 August 2026

Пока делюсь новостями подготовки к выбору проектов для работы 😉 🤑 Сколько брать за проект? - вот самый главный вопрос, ответ на который я ищу сейчас. Можно было бы просто посмотреть рынок, но тогда есть риск слишком поздно заметить, что производство начинает работать в убыток. Потому что себестоимость для разных команд и разной глубины проработки будет разная 💥 Да и отвечать на вопрос "почему так дорого" или понять

👍61😱1

5 Jul 2026, 10:11 UTC819 views10 reactionsread 7 August 2026

Учу своих детей совместно делать небольшие проекты) Старший сын делает монтаж видео, младшая дочь играет в игры и по-блогерски озвучивает, а средняя берет на себя роль ассистента стилиста (следит за опрятным видом сестренки в кадре) ☺️ Вот, что у них получилось в качестве первой работы https://youtu.be/W8z7ZtBIEz4?si=sQlub7I6yxdatn8T Нейросети помогают сыну в самостоятельном освоении видеомонтажа)

6🔥4

1 Jul 2026, 17:04 UTC899 views4 reactionsread 7 August 2026

Основная проблема посчитать и протестировать, как именно обучающие курсы превратятся в чистую прибыль 🤯 Причем для всех участников: - для студентов; - для заказчиков; - для команды; - для меня. Можно, конечно делать курсы "для души", но это не то пальто 😁

3💯1

30 Jun 2026, 14:25 UTC914 views13 reactionsread 7 August 2026

Как я готовлюсь к поиску EdTech-проектов: строю модель агентства, а не просто ищу работу Наконец-то я разложила по полочкам роли в современном EdTech. В теории всё красиво: методолог, проджект, продакт. В жизни — «всё смешалось... кони, люди...». В большинстве вакансий требуют совмещения функций без четких границ, а это риск для любой стороны. Сейчас я нахожусь на этапе соотнесения того, что я умею и хочу делать,

7👍4🔥2

27 Jun 2026, 06:55 UTC769 viewsread 7 August 2026

#Идея автоматизации производства контента на примере обучающих и методических материалов. Как думаете, взлетит?

Showing the 12 most recent of 20 posts we hold for @katerinaEAV_AI_EdTech. 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.

Citation-graph rank

Citation-graph rank — 1,079,656 of 1,480,944entries 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.

Mentions

Named by 1 registered channel — 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.

Names

Channels on the register whose handles appear in this channel's posts.

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

“Екатерина Ведяшкина | Нейросети и EdTech” (@katerinaEAV_AI_EdTech), 2,820 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/katerinaEAV_AI_EdTech.

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.