
Most peer review asks students to react to a whole artifact at once. They watch a ten-minute recorded pitch, a lab demonstration, or a language-practice clip, then write a paragraph that begins with "overall, this was good." The feedback floats above the work instead of touching it. We built peer review differently because the timeline is where the learning actually lives, and that is exactly where a reviewer's comment should land.

Ask a reviewer to summarize an entire video and you get generalities, because generalities are the only honest response to a blurred memory of twelve minutes. The reviewer cannot point, so they hedge. The author, receiving "work on your pacing," has no idea which thirty seconds dragged. Both learners walk away with the comforting sense that something was exchanged, and nothing changes in the next attempt.
Time-tagged review closes that gap. When a comment is pinned to 4:12, the author scrubs straight to the moment, sees precisely what the reviewer saw, and understands the note in context. Precision is not a nicety here; it is the entire mechanism that turns a reaction into a revision.
Inside Annoto, reviewers score against the rubric the instructor defines, but each criterion is applied where it occurs rather than in the abstract. A single clip might collect several anchored judgments:
Because the scores map to specific seconds, the author receives a coordinate, not a verdict. And because every rubric score syncs to the LMS gradebook, structured peer critique becomes assessable work rather than an ungraded courtesy exercise bolted onto the side of the course.
The reviewer learns as much as the author. To place a comment accurately, they have to hold the rubric in one hand and the evidence in the other, which is the same disciplined attention we want them to bring to their own work.
Reviewing well is a rehearsal for self-assessment. A learner who can locate the exact moment a peer's argument wobbles is far better equipped to catch their own.
All of this happens on the video instructors already assigned, through one-click LTI 1.3, with no separate tool for students to learn. The threaded exchanges document genuine Regular & Substantive Interaction, and the engagement analytics show us who reviewed carefully and who skimmed. Feedback stops being a report filed after the fact and becomes a conversation held exactly where it happens.
A strong first run starts with the rubric, and the test for each criterion is simple: could a reviewer point to a second on the timeline where it succeeds or fails? Keep to three or four observable criteria — a stated claim, use of evidence, pacing, delivery — and write each one as something a peer can actually see or hear. Vague qualities like professionalism will not anchor to a moment; observable behaviors will.
Calibrate before you assign. Review one sample clip together as a class, placing a few anchored comments and discussing what makes a note useful. Then set clear mechanics: each student reviews two peers, with a minimum number of anchored comments spread across the clip and a score for every criterion. Leave room between the review deadline and the revision deadline so authors have time to act on what they receive.
Finally, let the structure do the grading work. Rubric scores land in the gradebook automatically, and the analytics separate careful reviewers from skimmers, so you can grade the quality of critique as well as the quality of the original clip. One cycle of review followed by revision usually convinces skeptical students; assign a second round and the anchored comments get sharper on their own.
Related: In-Video Quizzes: Turning Passive Watching Into Active Recall, Why Passive Video Fails (and What Active Learning Fixes), and Bentley University: Annoto Across Every Online Learning Use Case.
New to Annoto? Start with What is Annoto?, or see it inside your LMS: Canvas, Moodle, Blackboard, and Brightspace.
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