CAHLR/pyBKT
Python implementation of Bayesian Knowledge Tracing and extensions
Is CAHLR/pyBKT beginner-friendly?
In the last 30 days, CAHLR/pyBKT merged 7 of 11 pull requests from outside contributors, and its maintainers usually reply within 1 day. 3 beginner-friendly issues are open now.
- Stars
- 283
- Forks
- 88
- Open beginner issues
- 3
- Indexed issues
- 20
- Avg merge
- 3h 37m
- Merged PRs (30d)
- 7
- Dominant language
- C++
- License
- MIT
- Last GitHub push
- Oct 9, 2026
- Latest indexed
- Sep 20, 2026
- Contributing guide
- No contributing guide
- Code of conduct
- No code of conduct
- Beginner labels
- No beginner labels indexed
How to contribute to CAHLR/pyBKT
- There is no contributing guide, so start from the README and a few recently merged pull requests to see how changes are proposed.
- Your contributions will be published under the project's MIT license.
- Pick one of the 3 open beginner-friendly issues below and comment that you want to work on it before you start.
Issues somebody may already be working on are listed last. List everything by date
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Difficulty 4/5 3-5 days Newbie friendliness 35/100
Maintainers usually reply within 1 day
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Difficulty 4/5 3-5 days Newbie friendliness 25/100
Maintainers usually reply within 1 day
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Difficulty 2/5 1-3 hours Newbie friendliness 82/100
Maintainers usually reply within 1 day
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Difficulty 3/5 1-2 days Newbie friendliness 55/100
Maintainers usually reply within 1 day
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Difficulty 3/5 1-2 days Newbie friendliness 50/100
Maintainers usually reply within 1 day
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Difficulty 3/5 1-2 days Newbie friendliness 62/100
Maintainers usually reply within 1 day
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Difficulty 5/5 Over a week Newbie friendliness 35/100
Maintainers usually reply within 1 day
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Difficulty 5/5 Over a week Newbie friendliness 25/100
Maintainers usually reply within 1 day
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Difficulty 1/5 Under an hour Newbie friendliness 45/100
Maintainers usually reply within 1 day
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Difficulty 3/5 1-2 days Newbie friendliness 20/100
Maintainers usually reply within 1 day
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Difficulty 4/5 3-5 days Newbie friendliness 25/100
Maintainers usually reply within 1 day
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Difficulty 4/5 3-5 days Newbie friendliness 35/100
Maintainers usually reply within 1 day
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Difficulty 3/5 1-2 days Newbie friendliness 35/100
CAHLR/pyBKT#49 · 2 comments · 1 reaction ·
Maintainers usually reply within 1 day
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Difficulty 4/5 3-5 days Newbie friendliness 35/100
Maintainers usually reply within 1 day
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Difficulty 4/5 3-5 days Newbie friendliness 25/100
CAHLR/pyBKT#45 · 1 comment · 1 reaction ·
Maintainers usually reply within 1 day
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Optional SQUAREM acceleration and beta priors for fittingPossibly taken A pull request linked to this issue is open or already merged. Open
Difficulty 5/5 Over a week Newbie friendliness 15/100
Maintainers usually reply within 1 day
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An unstable sort reorders responses that share an `order_id`, so the same data can give different fitsPossibly taken @arian-bozorgzad claimed this 3 days ago. Open
Difficulty 2/5 1-3 hours Newbie friendliness 85/100
Maintainers usually reply within 1 day
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C++ E-step returns the log-likelihood as an integer, so fitting stops earlyPossibly taken A pull request linked to this issue is open or already merged. Open
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
Maintainers usually reply within 1 day
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Publishing compiled wheels, and making scikit-learn optionalPossibly taken A pull request linked to this issue is open or already merged. Open
Difficulty 4/5 3-5 days Newbie friendliness 22/100
CAHLR/pyBKT#65 · 2 comments · 3 reactions ·
Maintainers usually reply within 1 day