Overview Leaderboard Methodology
Industry Report

Massive Open Online Courses

Large-scale online course providers offering university-style, often free or low-cost courses across many subjects with optional certificates.

Brands tracked: 39
Brands analyzed: 39
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 299
Total responses: 1,540
Top Brand Overall?
Coursera
96/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Khan Academy
96

Highest score on the LBA metric in this industry.

Authority Leader?
Coursera
100

Highest score on the Authority metric in this industry.

TOM Leader?
Coursera
100

Highest score on the TOM metric in this industry.

Coursera is the default answer in AI responses for Massive Open Online Courses

Coursera and edX together dominate AI responses for Massive Open Online Courses. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 39 Massive Open Online Courses brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Coursera
coursera.org
 88
100
100
96
2
edX
edx.org
 80
94
97
90
3
FutureLearn
futurelearn.com
 66
36
87
59
4
Khan Academy
khanacademy.org
 96
19
68
51
5
Udemy
udemy.com
 78
29
42
46
6
LinkedIn Learning
linkedin.com
 84
21
47
44
7
Udacity
udacity.com
 89
9
59
39
8
OpenLearn
open.edu
 62
9
37
29
9
MIT OpenCourseWare
mit.edu
 82
10
14
24
10
Alison
alison.com
 69
7
19
23
11
freeCodeCamp
freecodecamp.org
 90
9
9
21
12
Pluralsight
pluralsight.com
 88
9
9
21
13
Skillshare
skillshare.com
 79
8
11
21
14
Codecademy
codecademy.com
 85
8
8
20
15
Google Career Certificates
grow.google
 83
8
8
20
16
NPTEL
nptel.ac.in
 82
8
8
20
17
SWAYAM
swayam.gov.in
 67
7
14
20
18
MasterClass
masterclass.com
 74
7
7
18
19
OpenWHO
openwho.org
 69
7
7
17
20
Saylor Academy
saylor.org
 62
6
10
17
21
Stanford Online
stanford.edu
 69
7
7
17
22
openHPI
hpi.de
 64
6
6
16
23
Harvard Online
harvard.edu
 61
6
6
15
24
XuetangX
xuetangx.com
 58
6
6
15
25
FUN MOOC
fun-mooc.fr
 56
6
6
14
26
Stepik
stepik.org
 58
6
6
14
27
M
MiriadaX
miriadax.net
 52
5
5
13
28
NovoEd
novoed.com
 49
5
5
13
29
Kadenze
kadenze.com
 46
5
5
12
30
Academic Earth
academicearth.org
 45
4
4
11
31
Canvas Network
canvas.net
 42
4
4
11
32
OpenLearning
openlearning.com
 42
4
4
11
33
P
Polimi Open Knowledge
polimiopenknowledge.it
 34
3
3
9
34
Open2Study
open2study.com
 31
3
3
8
35
EduOpen
eduopen.org
 27
3
3
7
36
iversity
iversity.org
 23
2
2
6
37
Veduca
veduca.org
 15
2
2
4
38
MexicoX
mexicox.gob.mx
 11
1
1
3
39
Federica Web Learning
federica.eu
 0
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 299 shared Massive Open Online Courses prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 299 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →