Learners submit a video. Classmates review it inside the player, attaching every comment, question and video reply to the exact moment it refers to. Critique becomes specific, the author sees precisely what to change, and the reviewers learn by watching closely.
Time-coded peer review removes the translation step between a comment and the moment it describes.
A reviewer comments while watching, and each remark sits at the second it describes.
When the author replays their submission, every note shows up in context.
Built with courses where judging work is part of learning to do it.
Learners upload, classmates review in the player, instructors oversee from one dashboard.
The learner's video plays in the player they already use. Beside it, the peer review thread runs in time order, and every entry carries the timestamp it was written at. Click a timestamp and the video jumps there.
Reviewing is not only a service to the author. Done well, it teaches the reviewer just as much.
Peer review in Annoto is built from the same comment layer your learners already use, with the controls an instructor needs to keep a round honest, focused and gradable.
Every comment, question and reply is stamped with the moment it was written at. Clicking the timestamp moves the video there, for the author and for every later reader.
Reviewers can record themselves, or their screen, as a reply. Demonstrating an alternative way to perform the skill says more than a paragraph, and nothing needs to be downloaded.
Let learners post anonymously. Only instructors see who wrote what, so honest critique is possible without social cost and accountability stays with the course team.
Turn on Subjective Critical Thinking for a prompt and learners cannot see others' replies until they post their own, and cannot edit or delete afterwards. Each review is original thought.
Guide learners on what to focus on, highlight model feedback with the Educator's thumbs up, and delete off-topic comments from the widget or from the dashboard.
Hold replies for review and publish them together once everyone has responded, or restrict the thread to replies on the instructor's prompts so the round stays on task.
Instructors are notified when learners reply, so a review round moves forward without anyone refreshing a page, and the instructor can answer at a time that suits them.
Run the round as a native LMS peer review assignment, keep your rubric, and reuse Annoto's Assessment Criteria library across courses so grading rules stay consistent.
Peer review on video fits any course where the learning outcome is a performance: something a person does, in time, that can be watched and improved.
Learners submit a recorded talk. Peers mark where the argument loses structure, where delivery weakens, and where a transition works. Because each mark sits on the timeline, the speaker can rewatch the exact ten seconds a reviewer meant and compare it with a stronger passage the same reviewer praised.
Student teachers review one another's lessons and flag classroom decisions as they happen: how instructions were given, how a transition was managed, when a question was left hanging. Reviewers practise the observational skill their own mentors will apply to them, and the instructor sees every thread from the dashboard.
Nursing, medical and allied-health programmes record simulations and let peers tie feedback to specific steps in a procedure or specific moments in a patient conversation. Anonymous review and hidden-until-posted replies keep the critique candid, and the instructor's comments set the clinical standard.
Sales and customer-facing teams record role-plays, and colleagues review objection handling, discovery questions and closing at the moment each occurs. Video replies let an experienced colleague show an alternative approach, and managers can see who reviewed whom and how thoroughly.
The round runs inside the assignment your LMS already has. Annoto adds the time-coded layer on top of the video and the oversight the instructor needs.
The learner records or uploads their video through the course assignment. Annoto opens on top of it inside the LMS, on your existing video platform, so there is no new tool for learners to learn and nothing to install. Where it helps, the author can add their own reflection on the recording before anyone else sees it.
Peers watch and comment at the moments that matter, in text or as a recorded video or screen reply. The instructor's prompt sets what to look for. Anonymity, hidden-until-posted replies and managed comments shape the round so that every review is candid and independent, and the whole thread stays on the video.
The author replays the submission with the feedback in place, replies where they disagree and notes what they will change. The instructor reviews new comments from the dashboard, highlights the best ones, and grades in the LMS with the rubric the course already uses. Results stay in the gradebook; the discussion stays on the video.
The workflow is simple. The quality of a round depends on a few habits that experienced instructors share, and each one is easier to keep when the feedback is time-coded.
Review one sample video together before real submissions arrive. The instructor leaves a handful of time-coded comments, the class compares theirs against them, and the standard for depth is set. One precise comment tied to a moment is worth five that say nice job.
Tell reviewers what to focus on in the instructor prompt and roughly how many comments you expect. Time-coded evidence makes thoroughness visible: a reviewer who pointed at four moments and proposed alternatives is easy to tell apart from one who wrote a general paragraph.
Ask authors to reply to two or three comments with what they will change. Where the course allows a second submission, the pair of videos becomes evidence of growth, and the same time-coded thread shows whether the feedback was acted on.
The Annoto Analytics and Insights Dashboard reports, per learner, how much of each submission they watched and how many comments, replies and notes they wrote. That answers the two questions instructors ask first: did the reviewers actually watch the whole video, and did everyone contribute. An unread-comments view shows which videos have new feedback since the last visit, so reviewing a round means reading only what is new.
The full discussion on every submission is one click away from the dashboard, with the option to reply or remove a comment without opening the course. Because every entry is time-coded, spot-checking a review for depth takes a minute: you can see whether a reviewer pointed at moments or wrote generalities.
Average share of the submission each reviewer watched before commenting.
Comments, replies and notes written by each reviewer on one submission.
Activity on one submission, as shown on the video's page in the dashboard.
Annoto connects through LTI 1.3 and provides documented student video submission workflows for Canvas, Moodle, Blackboard and Brightspace (D2L), including peer review and skill assessment setups that use the LMS's own assignment and grading tools.
Set up the video submission and the peer review as a native assignment in Canvas, Moodle, Blackboard, Brightspace or Open edX. Grading happens with the LMS rubric, and Annoto's gradebook sync carries video activity outcomes into the gradebook without an export step.
Annoto runs as a layer over Kaltura, Panopto, Wistia, YouTube and Vimeo, so learner submissions and peer feedback live on the video platform your institution already manages. Video and screen replies are recorded in the browser, with nothing to download.
Lumo, Annoto's AI companion for education, can suggest evaluation prompts, ask learners for evidence-based justifications and provide structured feedback guidance, so a review round starts with clear expectations. Instructors keep the final word on everything learners see. Learn about Lumo AI
“In an online class, Annoto accomplishes many of the same goals for discussion as an in-person class. I highly recommend it to other instructors!”
Book a 20-minute demo and watch time-coded peer review work inside your LMS, on your own video platform, with the anonymity, moderation and grading options your course needs.