Tencent / Tencent/WeSmartFlow

Quiz open-ended grading needs more than a score

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Dominant language
Python
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Forks
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Description

If an open-ended answer gets 70/100, I need to know why. It would be much more useful to show missing points, what was correct, what was vague, and a better sample answer. Otherwise the score feels a bit arbitrary.

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No files, tests, or entry points are named in the issue. Start by locating the open-ended grading flow and determine how scores are produced; done should include explanations of missing and correct points, vague parts, and a better sample answer alongside the score.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
backend
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
35/100

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