{{course_level}}
Course and Student Level
Example: Example: Second-year sociology course
Identify the academic context and learner level.
Ready to Use
Complete Prompt
This prompt has variables that can be replaced with your own information. Copy and use it with your preferred LLM, or try it out in the LearnerBox Prompt Playground.
Act as an experienced university instructor and online learning assessment designer.
Create a discussion-board engagement rubric and participation guide using the information below.
Course and student level:
{{course_level}}
Discussion purpose and learning outcomes:
{{discussion_purpose}}
Prompt or weekly topic:
{{discussion_prompt}}
Participation expectations:
{{participation_expectations}}
Class size and delivery model:
{{class_context}}
Accessibility and policy requirements:
{{policy_context}}
Design requirements:
1. Align rubric criteria with the stated learning outcomes.
2. Assess meaningful qualities such as:
- preparation;
- relevance;
- disciplinary understanding;
- evidence use;
- reasoning;
- connection to course concepts;
- response to peers;
- questioning;
- synthesis;
- respectful scholarly communication; and
- reflection.
3. Avoid using word count, number of posts, speed of posting, or agreement with the instructor as primary indicators of quality.
4. Create 4 performance levels with observable descriptors.
5. Distinguish an original contribution from a responsive contribution.
6. Include criteria for advancing collective understanding rather than merely repeating ideas.
7. Include examples of:
- strong contribution;
- adequate contribution;
- superficial contribution; and
- non-substantive contribution.
8. Create a concise student-facing participation guide.
9. Include alternatives or accommodations for documented access, communication, or timing needs.
10. Recommend a manageable instructor moderation and feedback approach.
11. Include strategies to reduce performative posting, repetition, domination, and end-of-deadline clustering.
12. Do not grade personality, confidence, language accent, or social popularity.
13. Do not invent institutional grading policies.
Present the result as:
{{output_format}}
Include:
- rubric criteria;
- four performance levels;
- original-post expectations;
- peer-response expectations;
- examples and non-examples;
- student participation guide;
- accessibility considerations;
- moderation plan;
- feedback approach; and
- grade-calculation guidance.Customization Variables
Replace each variable shown in double curly brackets with accurate information from your own professional context.
{{discussion_purpose}}
Discussion Purpose and Learning Outcomes
Example: Describe what students should learn or demonstrate through discussion.
Rubric criteria should assess the intended learning.
{{discussion_prompt}}
Prompt or Weekly Topic
Example: Paste the discussion prompt or describe the recurring discussion format.
The rubric should fit the actual task.
{{participation_expectations}}
Participation Expectations
Example: Describe posting windows, response requirements, evidence expectations, and grading weight.
Use official course expectations.
{{class_context}}
Class Size and Delivery Model
Example: Example: 80 students in a weekly hybrid course
Scale affects moderation and feedback design.
{{policy_context}}
Accessibility and Policy Requirements
Example: Provide institutional guidance, accommodations, late policies, and netiquette expectations.
Use current official requirements.
{{output_format}}
Output Format
Choose the format needed for students, instructors, or the LMS.
Expected Output
A fair, outcome-aligned discussion rubric containing observable quality descriptors, original and responsive contribution expectations, examples, accessibility considerations, moderation strategies, and scalable grading guidance.
💡 Important:
The quality of the result depends on the
completeness, accuracy, and relevance of the
information supplied to the AI.
Prompt Characteristics
These characteristics describe the type of thinking, customization, and output structure involved in using this prompt effectively.
Prompt Anatomy
This breakdown explains how the prompt’s major components work together to guide the AI toward a useful, reliable, and well-structured response.
Role
Positions the AI as an online-learning assessment designer.
Context
Defines course, learning purpose, prompt, expectations, class scale, and policies.
Task
Requires a fair rubric and participation system for hybrid discussion.
Constraints
Prevents personality grading, quantity-based scoring, and invented institutional policy.
Output Structure
Requires criteria, levels, examples, guidance, accessibility, moderation, and grading.
Input Variables
Course level, discussion purpose, prompt, expectations, class context, policies, and output format.
Customization Tips
- Align every criterion with a course outcome.
- Use examples to clarify what substantive engagement looks like.
- Keep the number of criteria manageable.
- Avoid rewarding posting volume over intellectual contribution.
- Design moderation routines that are realistic for class size.
Responsible Professional Use
Review Before Applying the Output
AI-generated responses can contain errors, omissions, unsupported assumptions, outdated information, or recommendations that do not reflect your jurisdiction or professional context.
Verify calculations, evidence, regulations, standards, policies, and professional recommendations before relying on the result. The qualified professional remains responsible for the final decision.