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Perusall uses machine learning algorithms with linguistic capacity to imitate a human instructor and create predictive scores. The quality of the annotations or comments of the students might be included with the Perusall score. This isn't mandatory, as sometimes the annotations are counted as participation points.
Check with your instructor to know specific annotation quality requirements.
For more information on the quality of annotations, view this article for example scoring criteria: Perusall Scoring Examples
1. Here's an example of a great quality annotation.
A response such as:
"Particles in close proximity are either attracted to or partially repelled by other particles..."
Is better than:
- Wow, this makes sense.
- This opened my perception.
- That's great.
Responding in paragraph length and giving concrete details in your response will generate a higher annotative score when being graded by quality.
The instructor can:
- Adjust when the score is released to students.
- Chose how they want Perusall's algorithm to interact with the course.
- Set scoring criteria.
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