Review Assignments: You will receive up to 3 review requests per Work project once you have submitted your own draft.
If by the end of the course you have received fewer than 3 review requests, no requests, or too many requests please contact the teaching assistant.
Peer Review Tool: You must complete 3 peer reviews using the feedback section in CG Scholar. Sometimes this may be only 2 reviews and we will compensate for the system points.
To complete your review: Go to Notifications Tab>>Feedback Request>>Click on the “view work” request and it will open a tab in Creator. Remember name and close tab. Reopen by going to Works>>Click on name of work.
Once your work to review is open, on the bottom right in Creator click Feedback>>Review work>>Click on orange likert scale to view each rubric. Try to write at least 50 words for each review covering the rubric. After all boxes are complete and rated, move on to annotations. Tutorial Video Here
Annotations: Click on Annotations in the Feedback tab>>Choose text you want to comment on, and then click Create Annotation and then Add.
Submission: In order to submit, at least 15 annotations must be included. 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. 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.
Review content: 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 Submission: Wait until you have completed all pending reviews before submitting them. More ideas might come to you while you review another work.
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 a work or the reviews you receive(e.g. plagiarism, offensive reviews), please inform the teaching assistant or instructor.

Go to your work in Creator>>Feedback>>Reviews>>Results Use drop down menu if needed for multiple reviews.

To edit your work, it is good to open 2 windows so you can see the review

Can’t find annotations… Make sure you are on the version you sent for peer review. Go to About this Work>>Versions>> and choose the original version you sent. Then go to Feedback>>Annotations to check to see if they are listed.

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.

The Self-Review should be completed prior to your final submission. This is an opportunity to reflect on the improvements you have made to your work in response to the AI and Peer Reviews. This is completed as Update 5 and addresses both the peer and AI review processes.

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: