Submitting Your Work for Peer Review: Please follow this step-by-step guide for submitting your work for peer review.

Review Assignments: You will receive up to 3 review requests via CyberScholar once you have submitted your own draft. Here is a step-by-step guide to help you get started with the peer review process. If you have received fewer than 3 review requests, no requests, or too many requests, please contact one of the teaching assistants.
Annotations: Make sure at least 15 annotations are included. The annotations grading requirement is 20. Only 5 should be directed toward grammar or spelling.
Review Length and Ratings: Providing constructive feedback is going to be the most helpful to the authors. Please write strong explanations in your comments (at least 50 words or more). If you deduct a score explain why and how the author can improve. Even if you like a section and give full credit, explain what you liked and why. Be kind to peers in your reviews! Be as helpful as you can, offering them constructive suggestions. Feedback should be unique (not copy/pasted) and be directly relevant to the work under the review section. Comments must be tailored to a specific work.
Review content: Once you have all your annotations and rubric criterion comments ready, run a CyberFB that will give you feedback on the peer review you have populated (Step 10 in the guide above). Revisit your feedback after the CyberFB in order to improve your feedback on your peers’ work projects before you submit them.
Red Flags: Do not self-plagiarize or copy work from updates or other courses. This must be new work. If you notice any problems with the work or the reviews you receive(e.g. plagiarism, offensive reviews), please inform the teaching assistant or instructor.
Accessing Peer Reviews: To access the peer reviews you received on your work, follow steps 15 and 16 in the guide above

It is crucial that all students generate an AI review for their work using this feature before submitting the final version, as this can significantly impact their grades. Therefore, we strongly encourage all students to take advantage of this opportunity and produce an AI review to enhance the quality of their work and maximize their chances of achieving a higher grade.

Follow this order when doing reviews to refine your work:
1. AI Review: Use the Cyber Scholar AI tool to receive AI feedback and refine your work further.
2. Peer Review: Submit the first version (Draft) of your work for peer review to receive feedback from your peers.
3. Revision: Adjust your work based on peer and AI feedback suggestions and submit it.

The peer-review rubrics that we use in these courses are based on our Learning by Design research, and before that, the Multiliteracies project. This is grounded in an epistemologically based theory of learning, conceived as different kinds of knowledge processes, or “things you do to know.” In the first instance, this is an action-oriented view of knowledge and learning, and only secondarily a cognitively oriented theory.

The purpose of the rubric is to support creators and reviewers to think systematically about the fundamental knowledge orientations of their work. The coded annotations are in order to highlight specific examples of each generalization in the rubric. We are also analyzing these annotations as part of a research project exploring the potentials of artificial intelligence in education, in which users train the machine to detect higher-order thinking and epistemological moves.

Here is our “knowledge process” theory of learning in a visualization. The rubric is color-coded according to this visualization

See the Rubrics section below for work type-specific rubrics.

PDF version of the Knowledge Processes Rubric.  

PDF version of the Learning Module Rubric.

Here are some of the ways in which interpretive methods map against this rubric: