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treemarks.ai

Leaf grades. Course staff review.

Treemarks prepares conceptual feedback and grades. Your teaching team reviews and approves them.

  1. 01

    Setup

    Course and LMS setup.

  2. 02

    Assign

    Post the assignment. Build the rubric.

  3. 03

    Grade

    Leaf grades the work.

  4. 04

    Review

    Check work and results.

  5. 05

    Post

    Release grades and feedback.

This is what reviewing feels like.

Leaf grades first, then asks you the one question only a human should answer. One ruling prices the whole cohort.

Leaf

I just graded the midterm for you. 115 booklets are ready for review. One question first. Q2, Student 41: correct emissions factor, but combustion was never adjusted to the total fuel cycle. Is this a supporting concept error or an execution error?

You

Supporting concept. The pre-combustion boundary is the point of Q2.

Leaf

Applied. Your ruling set the tier for 83 similar responses. Here is the Q2 error distribution.

Illustrative conversation. Error counts come from a real, de-identified midterm cohort.

Feedback for students and course staff.

Student feedback

  • Score and earned rubric tier
  • What earned credit
  • The correction needed for full credit
  • Original work beside the feedback

Course feedback

  • Question and concept patterns
  • Edge cases and affected work
  • Staff decisions and rubric changes
  • Review and release status