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Case Study: Coursera delivers 45x more feedback with AI grading evaluated on Braintrust

Coursera Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Coursera
Industry
Education
Challenge
Fragmented, spreadsheet-based evaluation made it hard to validate AI grading before shipping to learners.
Headline result
Coursera reported roughly 45x more feedback with AI grading, a 16.7% increase in course completions, and a 90% learner satisfaction rating after building its evaluation process on Braintrust.

Key results

45x
More feedback with AI grading
16.7%
Increase in course completions
within a day of peer review
90%
Learner satisfaction rating
1 min
Grading turnaround time
learners receive grades within 1 minute of submission

The challenge

Coursera's AI grading and feedback initiative relied on fragmented, offline evaluation using spreadsheets and manual human labeling, with teams writing separate scripts and lacking a shared way to collaborate. This made it difficult to validate AI features with confidence before shipping them to learners.

The solution

Coursera built a structured evaluation process on Braintrust: defining success criteria up front, curating datasets that combine real-world and synthetic edge-case examples, applying hybrid scorers that pair deterministic checks with LLM-as-a-judge, and iterating with online monitoring and offline batch testing.

The results, in context

Coursera reported that learners now receive grades within about one minute of submission and roughly 45x more feedback through AI grading, alongside a 90% learner satisfaction rating. The company also reported a 16.7% increase in course completions within a day of peer review.

Products used

Braintrust Braintrust (evals, datasets, scorers)