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 11 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
24 measurements spanning 90 days, net -117. 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 9,539–9,692 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 24
Measured (UTC)
Subscribers
Change
5 Nov 2026, 05:36
9,557
-7
2 Nov 2026, 12:55
9,564
-5
30 Oct 2026, 04:57
9,569
-2
26 Oct 2026, 21:45
9,571
+10
23 Oct 2026, 14:34
9,561
-7
20 Oct 2026, 10:35
9,568
-11
17 Oct 2026, 01:21
9,579
-8
14 Oct 2026, 11:11
9,587
-13
11 Oct 2026, 02:57
9,600
-6
5 Oct 2026, 03:41
9,606
-4
26 Sept 2026, 01:00
9,610
+12
17 Sept 2026, 06:01
9,598
-10
13 Sept 2026, 03:16
9,608
-4
8 Sept 2026, 22:16
9,612
-21
3 Sept 2026, 23:21
9,633
-4
31 Aug 2026, 07:48
9,637
-1
26 Aug 2026, 02:55
9,638
-10
23 Aug 2026, 08:56
9,648
-6
19 Aug 2026, 13:53
9,654
-8
16 Aug 2026, 20:55
9,662
first reading
Engagement
61 posts held, back to 29 June 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 42 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
12.6%
avg views ÷ 9,557 subscribers
Avg views / post
1,200
18 posts measured
Reaction rate
1.74%
reactions ÷ views · ER floor
Posts in window
19
of 61 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. It is computed over the 14 of 18 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 5 November 2026
Posts held
61 (29 June 2026 – 5 November 2026)
Views total
21,673
Reactions total
317
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Nov 2026, 09:43 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
84
Videos
50
Links
109
Lifetime counters from Telegram’s own channel header, read 6 November 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
1m 07s
Average length
1m 07s
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
1,076 reactions across 54 posts, in 10 distinct kinds. The most used accounts for 76.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
818
76.0%
👍
167
15.5%
😍
19
1.77%
👌
18
1.67%
🏆
16
1.49%
👎
14
1.30%
💯
9
0.836%
🙏
8
0.743%
👏
4
0.372%
😢
3
0.279%
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 54 of the 61 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 1,076 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 61 most recent posts we hold, published 29 June 2026 to 5 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: 8 of 19 posts held from the last 30 days (42.1%) 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).
رایتینگ رو تموم کردیم. حالا نوبتِ شکارِ کلمههای تکراریه!
هر کلمهای دو بار دیده بشه، باید یه جایگزین پیدا کنه. انگار بار دوم بدون دعوت وارد متن شده.
ولی قبل از عوضکردن، یه لحظه صبر کنیم.
فرض کنیم نوشتیم «بعضی بچهها به کمک بیشتری نیاز دارن». بعد برای تنوع، children رو میکنیم students.
این دو گروه با هم همپوشانی دارن، ولی یکی نیستن. بعضی بچهها هنوز مدرسه نمیرن؛ بعضی دانشجوها هم بچه نیستن.
پس از خودمون بپرسی…
تدریس حرفهای فقط به دانستن تکنیکها محدود نمیشود؛ مهم این است که بدانیم چرا، چه زمانی و چگونه تصمیم بگیریم.
در Teacher Development Program – Intensive فرصتی برای بازنگری، بهروزرسانی دانش و توسعه مهارتهای حرفهای تدریس فراهم کردهایم.
🌱 چهار هفته برای تصمیمهای آگاهانهتر در کلاس.
📩 مشاوره تخصصی
✅ ثبتنام در دوره
@MMT_IELTSHousesupport
وقتی واقعیت مطابق میل ما نیست، آرزو میکنیم!
تا حالا فکر کردهاید کلمهی wish از کجا آمده و چرا در زبان انگلیسی اینقدر با دنیای خیال و واقعیت سروکار دارد؟
این کلمه ریشهای بسیار قدیمی دارد. از فعل wȳscan در انگلیسی باستان آمده و ریشههای دورترش به خانوادهای از واژهها میرسد که با میل، اشتیاق و خواستن ارتباط داشتهاند.
اما چیزی که برای ما زبانآموزها جالب است، فقط تاریخچهی این کلمه نیست؛ رابطهی آن با واقعیت است.…
📚 Teacher Development Program – Intensive
یک برنامه فشرده ۴ هفتهای ویژه مدرسان زبان که میخواهند دانش حرفهای خود را بهروز کنند، چالشهای کلاس را بهتر تحلیل کنند و تصمیمهای آموزشی آگاهانهتری بگیرند.
🔹 ۴ هفته آموزش فشرده
🔹 ۲۴ جلسه زنده
🔹 تمرینها و تکالیف حرفهای
🔹 پروژه پایانی
💳 امکان پرداخت چهارمرحلهای از طریق دیجیپی فراهم است.
📌 مشاهده جزئیات دوره و ثبتنام:
https://eltmmt.ir/Product/Details/1039
داستان ۴ دقیقهای الکاپون رو با صدای زیبای نلسون لاور بشنوید.
از لینک زیر هم فایل صوتی و متنی این پادکست را دانلود کنید.
https://eltmmt.ir/Blog/al-capone-the-story-of-scarface-b2
من توی کلاس به شوخی میگم شرطی نوع دوم یه راهه برای گفتنِ چیزهایی که زندگی فعلاً حاضر نیست تحویلمون بده!
همهمون یه عالمه «دلم میخواست» داریم. زبان بهمون اجازه میده این خواستهها رو از توی سرمون بیاریم بیرون، بهشون جمله بدیم و یه لحظه ببینیم زندگی اگه جور دیگهای بود، چه شکلی میشد.
خیلی از زبانآموزهام میگن با این توضیح، گرامر براشون آشناتر میشه. انگار مدتها حرفش رو داشتن، فقط دنبال راهِ گفتنش میگشتن.
البته…
در جلسهٔ کاری میتوانیم دربارهٔ یک پروژهٔ پیچیده توضیح بدهیم. اما در کلاس زبان، برای گفتنِ «جلسه را بگذاریم فردا» دنبال کلمه میگردیم.
کلافهکننده است. در ذهنمان حرفهای زیادی داریم، اما در انگلیسی، چند جملهٔ کوتاه.
گاهی همین فاصله باعث میشود سکوت کنیم. جملهٔ سادهای بلدیم، اما به نظرمان زیادی ساده است؛ انگار اندازهٔ خودمان نیست.
مثلاً میتوانیم بگوییم:
Can we meet tomorrow?
اما آن را کنار میگذاریم، چون دنبال جمل…
👍18❤1🏆1💯1
Signed Mohammad Mohammaditabar
Showing the 12 most recent of 61 posts we hold for @MMT_IELTSHouse. 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
@MMT_IELTSHouse edited 5 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
8 August 2026
Most recent edit
18 August 2026
Posts recorded as deleted after publishing
We recorded 2 posts on @MMT_IELTSHouse as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
9 August 2026
Most recent seen missing
12 August 2026
Median time before seen missing
31 hours
Seen missing in the last 30 days
0
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 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.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@MMT_IELTSHouse named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@mohammaditabar_efl named in 79 posts, 8 August 2026 – 4 November 2026
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.
SaharCast🎙 @SaharCast · 34,082 Telegram ranks this channel #14 of 90 here — alongside 89 others — read 3 September 2026
Dr Ahmadian @drmjahmadian · 90,586 Telegram ranks this channel #15 of 93 here — alongside 92 others — read 17 August 2026
AFARINESH | خانه آیلتس آفرینش @afarinesh · 79,292 Telegram ranks this channel #21 of 87 here — alongside 86 others — read 19 August 2026
Luminous.english @english_prism · 38,919 Telegram ranks this channel #32 of 80 here — alongside 79 others — read 30 August 2026
IELTS Journal @ieltsjournalchannel · 50,707 Telegram ranks this channel #43 of 85 here — alongside 84 others — read 25 August 2026
Visa Mondial | ویزا موندیال @visamondial · 25,816 Telegram ranks this channel #48 of 62 here — alongside 61 others — read 15 September 2026
Spark IELTS Assistant @sparkIELTSspeaking · 33,515 Telegram ranks this channel #61 of 89 here — alongside 88 others — read 4 September 2026
IELTS BANK @ieltsbank · 22,636 Telegram ranks this channel #67 of 93 here — alongside 92 others — read 20 September 2026
IELTS Channel @PARGARIELTS · 25,803 Telegram ranks this channel #67 of 87 here — alongside 86 others — read 14 September 2026
Soheyl English | انگلیسی کاربردی با سهیل سام @soheyl_english · 58,762 Telegram ranks this channel #71 of 87 here — alongside 86 others — read 23 August 2026
This channel appears in 10 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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“IELTS House - Writing and Speaking” (@MMT_IELTSHouse), 9,557 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/MMT_IELTSHouse.
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.