MIT Open Learning ✓

@mitopenlearning · Cambridge, MA · joined 12 Jun 2018

Transforming teaching and learning around @MIT and the globe. Online offerings from @mitocw, @MITxCourses, @MITxPRO, and more on MIT Learn: https://t.co/Ra69l1V7yn

17 077Followers

745Following

5 141Posts total

7.3KViews on collected posts

Últimas publicaciones

MIT Open Learning ✓@mitopenlearning7 Sep

What happens when passion becomes purpose? ✨ Gustavo Barboza traded a college classroom in Colombia for a life of adventure, serving in the French military before finding his way back to learning. Today, he's working toward an electrical engineering degree — and @mitocw has htt

338 views · 4 likes · 0 reposts · 0 replies Open on X →

MIT Open Learning ✓@mitopenlearning6 Sep

@mitopenlearning 1 4 views · 0 likes · 0 reposts · 0 replies Open on X →

MIT Open Learning ✓@mitopenlearning6 Sep

Do you know Jehova turned Satan evil just to kill me and send me to earth powerless and take over my Heaven ,because imthe Holy spirit and he got ride of me so he could do evils like giving kids diseases and genetic defects. And send them to Hell if they sin and not educate 524 views · 0 likes · 0 reposts · 1 replies Open on X →

MIT Open Learning ✓@mitopenlearning6 Sep

@mitopenlearning MIT teaching ML is a rare edge since formal education lacks hands-on agent deployment data. 1 views · 0 likes · 0 reposts · 0 replies Open on X →

MIT Open Learning ✓@mitopenlearning5 Sep

@mitopenlearning small but important 36 views · 0 likes · 0 reposts · 0 replies Open on X →

MIT Open Learning ✓@mitopenlearning5 Sep

Thinking about adding machine learning to your engineering toolkit? Start by hearing from the person who teaches it. On Wednesday, September 9 at 12pm ET, MIT professor Youssef Marzouk will walk through MIT xPRO's machine learning, modeling, and simulation: engineering https://t

2.2K views · 65 likes · 15 reposts · 3 replies Open on X →

MIT Open Learning ✓@mitopenlearning4 Sep

When a university needs to train 15,000 students in AI fast, you adapt. Namibia University of Science and Technology did. Over 1,100 people moved from zero AI skills to confident practitioners in six months. Free resources. Strategic focus. Institutional change. Read the full

628 views · 7 likes · 2 reposts · 0 replies Open on X →

MIT Open Learning ✓@mitopenlearning3 Sep

Camera lenses are doing something far cooler than most people realize. Half the lens covered. Half the image gone? Actually, no. Jim Bales, associate director at @MITEdgerton, breaks down the physics of how lenses focus light, bend rays, and form complete images. Two minutes to

2:07

1.2K views · 30 likes · 8 reposts · 1 replies Open on X →

MIT Open Learning ✓@mitopenlearning3 Sep

@mitopenlearning #PublicSafety https://t.co/plOeaNNVmv

18 views · 0 likes · 0 reposts · 0 replies Open on X →

MIT Open Learning ✓@mitopenlearning2 Sep

Recognize. Relate. Integrate. MIT senior lecturer Laura Frawley's students use concept maps to show how they organize ideas, and the mapping itself is a way to study. Full episode of Open Seminar on MIT Learn: https://t.co/PjAn8YvQAS https://t.co/s2wz0czNdS

0:28

2.3K views · 52 likes · 12 reposts · 1 replies Open on X →

Frente a cuentas del mismo tamaño

10 publicaciones de los últimos 90 días, junto al rango de 10K–100K seguidores. por debajo de sus pares en alcance y en interacción.

Visualizaciones medianas431esta cuenta993mediana de 10K–100K

Alcance, %2.52%esta cuenta3.63%mediana de 10K–100K

Interacción, %0.78%esta cuenta1.92%mediana de 10K–100K

Métrica	Esta cuenta	Mediana de 10K–100K	Proporción
Visualizaciones medianas por publicación	431	993	0.43×
Alcance (visualizaciones ÷ seguidores)	2.52%	3.63%	0.70×
Tasa de interacción	0.78%	1.92%	0.41×

Otras cuentas de este rango → Comparar con otra cuenta → Cómo se construyen estas referencias →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

2.3K2 Sep

183 Sep

1.2K

6284 Sep

2.2K5 Sep

16 Sep

524

3387 Sep

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

2.79%2 Sep

0.00%3 Sep

3.31%

1.43%4 Sep

3.79%5 Sep

0.00%

0.00%6 Sep

0.38%

0.00%

1.18%7 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.92%.

What the audience does

Likes54.3%158 in total

Reposts12.7%37 in total

Replies2.1%6 in total

Quotes0.7%2 in total

Bookmarks30.2%88 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Últimas publicaciones

Frente a cuentas del mismo tamaño

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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