Key Takeaways: Team Dynamics and Adjustment Factor

This guide summarises the key elements academics should understand when reviewing peer-evaluation data, including the Adjustment Factor (AF), Exceptional Conditions, and common interpretation pitfalls. Short examples are included for clarity.

 

What the Adjustment Factor (AF) Shows

Adjustment Factor (AF) compares a student’s average peer rating with the team’s overall average.

It answers the question: “Was this student rated higher or lower than the team norm?”

Adjustment Factor (AF) Value Interpretation

• ≈ 1.00 - In line with team norms
• > 1.10 - Rated higher than peers → strong perceived contribution
• < 0.90 - Rated lower than peers → possible under-performance or concern

 

Using AF Together with “Exceptional Conditions”

Exceptional Conditions reveal why a score might be unusually high/low. Adjustment Factor (AF) + flags must always be read together.

 

Overconfident

• Self-rating is ≥1 point higher than peers
• Team rates B: 2.6; self-rating: 4.0 → AF ~1.05
• AF may look normal but self–peer gap is the issue
  
  

Manipulator

• Self rated ≥4, all others rated low
• C rates self: 4.5; peers: 2.0 → AF inflated to 1.30
• Ignore AF; check for unfair rating behaviour
  
  

Low Performer

• Peers rate <2.5
• Team average: 3.5; D: 2.1 → AF = 0.60
• A reliable indicator of contribution issues

Conflict

• One student rates another ≤2 while others ≥3
• One low score among otherwise high scores
• Issue is interpersonal, not performance
  
  

Clique

• Subgroups inflate each other’s scores
• Two students give each other 4.5, others 2.0
• AF becomes unreliable → check group dynamics

 

Comments Matter as Much as Numbers

Peer comments often reveal:

• workload distribution
• attendance/communication issues
• interpersonal challenges
• or genuinely strong contributions

Use comments to validate AF and flags.

 

Be Careful with Self-Ratings

Self-ratings are influenced by:

• confidence levels
• cultural norms
• personality

They are not reliable for grading decisions; rely mainly on peer ratings + patterns.

 

Look at Rating Distribution, Not Just Averages

Averages can hide problems.

Example:

Student E receives: 3, 3, 3, 1

Average = 2.5 → but the single “1” flags potential Conflict or personal issues.

Patterns > averages.

 

AF and Flags Are Diagnostic, Not Automatic Penalties

Buddycheck is designed to:

• signal issues
• reveal dynamics
• support fair conversations

It is not intended to penalise students solely based on low scores.

Best practice: confirm patterns through comments, multiple teammates, observed behaviour from presentations, recorded meeting minutes, each member’s assigned component, and timely follow-ups.

 

Cultural and Social Bias Awareness

Students may:

• underrate themselves (self-effacement)
• overrate themselves (self-enhancement)
• give “friendship scores”
• avoid giving negative feedback

Remind students to rate behaviours, not popularity.

 

Practical Checklist

1. Look for outliers in Adjustment Factor (AF)
   Values <0.85 or >1.15 are worth reviewing.
   
   
2. Cross-check with Exceptional Conditions
   Flags explain the reason behind unusual AFs.
   
   
3. Read comments carefully
   Consistent comments across teammates are strong evidence.
   
   
4. Investigate before adjusting grades
   Especially when manipulator, conflict, or clique flags appear.
   
   
5. Use results to guide feedback conversations
   Example: “Your peers noted challenges in communication; let’s discuss how we can support you.”

 

Summary

Use the Adjustment Factor to spot rating outliers, use Exceptional Conditions to understand why, and always confirm patterns through comments and rating distributions before making decisions.