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Professor
Turn written AI policy into enforceable controls
Translate instructional AI guidance into configured capabilities students encounter directly in the RedAPPL workspace.
An early-stage product direction. The interface and scenario below are illustrative, not production screenshots or customer results.
RedAPPLSample workspace
From policy to configuration
“Students may brainstorm ideas, but must write their own response.”
↓ Instructor-reviewed configuration
BrainstormingAllowed
Final-response draftingRestricted
Why it matters
Written guidance can leave room for different interpretations.
Capability settings can make instructional intent more explicit.
Instructors should review the configuration before students encounter it.
Designed workflow
How it works
- Start with the assignment's written AI guidance.
- Map that guidance to specific capabilities and review the interpretation.
- Preview the configured student experience before publishing.
Example scenario
Put it in context.
An instructor allows idea generation but wants students to write their own analysis.
A sample interaction to explain the intended experience.
- Example request
- Configure the policy: brainstorm ideas, but do not write the final response.
- Applicable policy
- Brainstorming is permitted; generating submission-ready prose is restricted.
- Illustrative RedAPPL behavior
- RedAPPL is designed to connect that distinction to the capabilities in the student workspace.
- Intended next step
- Students encounter support aligned with the instructor's reviewed configuration.
Bring your university context to the conversation.
Request a demo or discuss how your institution could help shape RedAPPL as a design partner.