Gradescope vs Teachable Machine
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Gradescope is an assessment and grading platform for online and in class courses that supports paper based exams, PDFs, bubble sheets, programming assignments, and online assignments, using question by question workflows, rubrics, and analytics to speed up consistent feedback.
Google’s browser-based tool for training simple image, audio, and pose models without code. Exports to TensorFlow.js, TensorFlow Lite, and more for use on web and mobile.
Feature Tags Comparison
Key Features
- Question by question grading: Navigate submissions one question at a time to stay consistent and reduce grading context switching
- Dynamic rubrics: Build rubric items per question and apply feedback quickly while keeping point values adjustable when needed
- Assignment type coverage: Grade paper exams and student uploaded PDFs and instructor uploaded PDFs and bubble sheets and online assignments
- AI assisted answer groups: Group like answers for open response questions to review similar work together using the rubric
- Programming support: Use autograders for immediate feedback or manually grade code with inline comments and scoring rubrics
- Student workflows: Students upload PDFs or photos and can use a student mobile app for submission and viewing returned work
- No-code image audio and pose training
- Dataset capture with webcam or mic
- Live model preview in the browser
- Export to TensorFlow.js and Lite
- Starter projects and templates
- Ethics and data tips for lessons
Use Cases
- Midterm grading: Scan paper exams then grade question by question with a rubric so multiple TAs can work in parallel quickly
- Homework review: Collect student uploaded PDFs and apply consistent rubric feedback with quick edits that update past work
- Open response efficiency: Use answer groups to review like answers together for explanations and short essays at scale with less context switching
- Bubble sheet scoring: Create an answer key then auto grade bubble sheets and confirm marks before releasing results to students
- CS autograding: Run an autograder for programming assignments and provide immediate feedback while tracking scores per test
- Anonymous grading: Enable anonymous workflows during grading to reduce bias and reveal names only after grading is finalized
- Classroom projects to explain ML basics
- Interactive art and exhibit prototypes
- Sound event detectors for hobby projects
- Gesture-based controls for web apps
- Student research demos and fairs
- Accessible workshops without installs
Perfect For
instructors and professors, teaching assistants and graders, academic departments, instructional designers, assessment coordinators, IT and LMS admins, schools evaluating institutional licenses
teachers, students, hobbyists, and makers who want to learn ML concepts and build interactive demos without code or installs
Capabilities
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Need more details? Visit the full tool pages.