Feedback review is a critical quality control step in FeedForward. As an instructor, you review AI-generated feedback before it's released to students, ensuring it aligns with your teaching goals and maintains appropriate standards. This guide covers the review workflow, editing options, and best practices.
1. Student submits draft
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2. AI generates feedback
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3. Instructor notified
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4. Instructor reviews
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5. Instructor approves/edits
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6. Student receives feedback
Your central hub for pending reviews:
Feedback Review Dashboard
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Pending Reviews: 12
├── ENGL101 - Essay 1: 8 submissions
├── ENGL101 - Essay 2: 3 submissions
└── ENGL201 - Research Paper: 1 submission
Recent Activity:
• 3 new submissions in last hour
• 15 reviews completed today
• 2 flagged for attention
Quick Actions:
[Review All] [Filter] [Export] [Settings]
From Dashboard - Click notification badge - Select "Pending Reviews" - View all awaiting feedback
From Course - Navigate to course - Click "Assignments" - See review count per assignment
From Assignment - Open specific assignment - Click "Review Feedback" - See all submissions
When reviewing a submission:
┌─────────────────────────────────────────────────┐
│ Student: Jane Smith │
│ Assignment: Essay 1 - Personal Narrative │
│ Draft: 2 of 3 │
│ Submitted: 2 hours ago │
│ Word Count: 847 │
│ Processing Time: 45 seconds │
│ │
│ AI Models Used: │
│ • GPT-4: 3 runs (averaged) │
│ • Claude-3: 3 runs (averaged) │
│ │
│ Overall Score: 82% (B) │
└─────────────────────────────────────────────────┘
The review interface shows:
┌─────────────┬──────────────┬─────────────────┐
│ Student │ AI │ Instructor │
│ Submission │ Feedback │ Actions │
│ │ │ │
│ [Original │ [Generated │ [Edit Options] │
│ Text] │ Feedback] │ [Scoring] │
│ │ │ [Comments] │
│ │ │ [Approve/Reject]│
└─────────────┴──────────────┴─────────────────┘
Features for easier review:
AI feedback typically includes:
Overall Assessment:
Summary: Brief overview of submission quality
Score: Numerical/letter grade
Key Strengths: Top 2-3 positive aspects
Main Areas for Improvement: Top 2-3 concerns
Rubric-Based Evaluation:
For each criterion:
- Score (points/percentage)
- Specific feedback
- Examples from text
- Suggestions for improvement
Detailed Comments:
- Paragraph-level observations
- Writing mechanics notes
- Content-specific feedback
- Next steps recommendations
Understanding AI certainty:
Confidence Levels:
🟢 High (90-100%): AI very certain about evaluation
🟡 Medium (70-89%): Some uncertainty in scoring
🔴 Low (<70%): Significant uncertainty, careful review needed
Common Low-Confidence Triggers:
- Unusual formatting
- Mixed languages
- Creative/unconventional approaches
- Technical jargon
- Very short/long submissions
For high-quality AI feedback:
When modifications needed:
Score Adjustments: - Change overall score - Modify rubric scores - Add score justification - Override AI calculations ```
Personalize feedback:
Comment Options:
Location:
- Top of feedback (most visible)
- After specific rubric items
- Bottom summary
Types:
- Encouragement
- Specific guidance
- Resource links
- Meeting requests
Formatting:
- Rich text editor
- Bullet points
- Links
- Emphasis (bold/italic)
Example comment:
Instructor Note: Jane, I'm impressed with your improved
thesis statement! For your final draft, consider adding
one more supporting example in paragraph 3. Feel free to
visit my office hours if you'd like to discuss further.
When AI feedback is inadequate:
Options:
Regeneration Settings:
- Use Different Model: [Select]
- Adjust Temperature: [Slider]
- Add Context: [Text field]
- Focus Areas: [Checkboxes]
Additional Context Example:
"Student is ESL learner - provide more grammar
explanations and examples. Focus on article usage
and verb tenses."
Mark submissions needing follow-up:
Flag Types:
Academic Concern:
- Potential plagiarism
- Off-topic submission
- Significant regression
Student Support:
- Mental health indicators
- Request for help
- Technical issues
Technical Issue:
- Corrupted file
- Wrong assignment
- System error
Handle multiple submissions efficiently:
Select Multiple - Check boxes next to submissions - Or "Select All Similar"
Bulk Actions:
Available Actions:
✓ Approve all selected
✓ Add same comment to all
✓ Apply score adjustment
✓ Flag for later review
✓ Export for offline review
For experienced reviewers:
Quick Review Settings:
├── Show only essential info
├── Keyboard shortcuts enabled
├── Auto-advance after action
└── Batch similar submissions
Keyboard Shortcuts:
A - Approve
E - Edit
R - Regenerate
F - Flag
→ - Next submission
← - Previous submission
Organize your workflow:
Filter Options:
By Status:
- Unreviewed
- In progress
- Flagged
- Approved
By Score:
- High (85%+)
- Medium (70-84%)
- Low (<70%)
- Outliers
By Student:
- First-time submitters
- Multiple drafts
- Struggling students
- High performers
By Time:
- Oldest first
- Newest first
- Due soon
- Overdue
Maintain fair standards:
Review Similar Together - Group by topic - Compare approaches - Ensure fair scoring
Use Rubric as Guide - Reference criteria - Apply uniformly - Document exceptions
Track Patterns - Note common issues - Identify trends - Adjust instruction
Streamline your process:
Time Allocation: - Quick approve: 1-2 minutes - Minor edits: 3-5 minutes - Major revision: 10+ minutes ```
Use Templates - Common comments - Frequent corrections - Standard encouragements
Prioritize Reviews - Final drafts first - Struggling students - Time-sensitive items
Maximize learning impact:
Balance Criticism - Start with positives - Specific improvements - End with encouragement
Be Specific
❌ "Improve your thesis"
✅ "Your thesis 'Technology affects society'
is too broad. Try focusing on one specific
technology and its impact, such as 'Social
media has fundamentally changed how teenagers
form friendships.'"
Guide Next Steps - Clear action items - Resources to consult - Office hour invitations
When content concerns arise:
Off-Topic Work - Don't approve AI feedback - Add instructor comment - Request resubmission - Note in gradebook
Potential Plagiarism - Flag for investigation - Don't release feedback - Follow institutional policy - Document concerns
Personal Disclosures - Handle sensitively - Consider privacy - Offer support resources - Consult if needed
Common problems and solutions:
Garbled AI Feedback - Regenerate with different model - Check submission format - Manual feedback if needed
Missing Rubric Scores - Manually add scores - Check rubric configuration - Report to admin
Processing Errors - Resubmit for processing - Try different file format - Contact support
Track your review patterns:
Your Review Analytics:
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This Week:
Reviews Completed: 47
Average Review Time: 3.5 minutes
Edits Made: 23%
Regenerations: 5%
This Semester:
Total Reviews: 342
Quick Approvals: 65%
Major Edits: 15%
Regenerations: 8%
Flags: 12%
Efficiency Score: 87/100
AI identifies trends:
Detected Patterns:
Common Issues:
- Thesis statements (45% of edits)
- Citation format (30% of edits)
- Conclusion weakness (25% of edits)
Student Patterns:
- 5 students consistently low scores
- 3 students showing improvement
- 2 students possible support needs
Feedback Patterns:
- GPT-4 better for creative writing
- Claude-3 better for research papers
- Morning reviews 20% faster
Move feedback to gradebook:
Export Formats:
CSV:
- Student name
- Assignment
- Score
- Feedback summary
- Review notes
LMS Integration:
- Direct grade sync
- Feedback upload
- Rubric mapping
PDF Reports:
- Individual student
- Class summary
- Progress tracking
How scores become grades:
Score Mapping:
93-100% → A
90-92% → A-
87-89% → B+
83-86% → B
80-82% → B-
[continues...]
Custom Mappings:
- Curve adjustments
- Weighted categories
- Drop lowest
- Bonus points
Develop a consistent review routine - students appreciate timely, thoughtful feedback more than perfect feedback delivered late.
Remember that you're training AI to better understand your standards. Your edits and regeneration requests help improve future feedback quality.