Personalization Guide

Customize learning experiences and support diverse student needs

Published

July 19, 2026

Overview

Kai supports personalized learning by adapting quiz difficulty based on student performance and providing instructors with the data they need to tailor their teaching. This page explains the personalization features available in the app and how to use them effectively.

Why Personalization Matters

Benefits for Students: - Receive quiz content calibrated to their current level - Get targeted feedback on weak areas - Experience learning support that responds to their progress

Benefits for Instructors: - Identify struggling students early - Allocate support time efficiently - Track individual and group progress - Maintain engagement across diverse learners

Adaptive Quizzing

Kai’s pop quiz feature can adapt question difficulty based on how a student performs during a quiz session. When adaptive difficulty is enabled:

  • Students who answer correctly are challenged with slightly harder questions
  • Students who answer incorrectly receive questions at a more accessible level
  • The quiz ends when the student reaches mastery or the question limit

This means two students taking the same quiz may see different questions—this is intentional and normal behavior.

To disable adaptive difficulty (for a uniform quiz experience):

Dashboard → Quiz → Settings → Adaptive Difficulty → OFF
Enable "Same quiz for all students"

Student Experience Example

Student A (developing understanding of p-values):
1. Question (Medium): "What does p-value represent?" → Incorrect
2. Question (Easy): "Is p-value a probability?" → Correct
3. Question (Easy-Medium): "Which p-value is more significant: 0.03 or 0.08?" → Correct
4. Question (Medium): Definition question → Correct
5. Quiz ends after achieving mastery at appropriate level

Student B (strong understanding):
1. Question (Medium): Definition → Correct
2. Question (Medium-Hard): Interpretation → Correct
3. Question (Hard): Application scenario → Correct
4. Question (Hard): Complex analysis → Correct
5. Quiz ends with mastery at advanced level

Student Learning Profiles

Kai automatically tracks student performance data to build a picture of each student’s progress. Instructors can view this in the analytics dashboard, which shows:

  • Performance history across quizzes and assignments
  • Topic mastery levels (mastered, proficient, developing)
  • Engagement patterns (participation rate, resource usage)
  • Suggested focus areas based on recent performance

This information helps you have more targeted conversations with students and direct your support where it’s most needed.

Personalized Feedback

When Kai generates feedback on student quiz submissions, it adjusts the tone and detail based on context:

  • Students with lower scores receive more detailed explanations and suggested resources
  • Students with higher scores receive concise confirmation and optional challenge questions
  • All feedback is growth-focused and private to the individual student

Example Feedback Comparison:

Assignment: Problem Set on Hypothesis Testing
Question: "Calculate and interpret the p-value"

--- DEVELOPING STUDENT (Score: 55%) ---
Great effort on this problem set! Let's focus on building your
understanding of p-values.

For question 3, you calculated p = 0.08 correctly — nice work on the
calculation! However, the interpretation needs some adjustment. Remember:
a p-value tells us the probability of getting our result (or more extreme)
if the null hypothesis were true.

Key Point: Compare your p-value (0.08) to alpha (0.05). Since 0.08 > 0.05,
we FAIL TO REJECT the null hypothesis.

Try thinking of it this way: If p is low (< alpha), the null must go!
If p is high (> alpha), the null can stay!

Helpful Resources:
- Video: "Understanding P-values Intuitively" (8 min)
- Practice: "P-value Interpretation Quiz" (10 problems)

--- ADVANCED STUDENT (Score: 96%) ---
Excellent work. Calculations accurate, interpretations clear and precise.

Question 3: Consider discussing Type II error risk when p = 0.08 (close
to boundary).

Challenge: For your next assignment, try incorporating effect size measures
(Cohen's d) alongside p-values for more complete inference.

Student Progress Dashboards

Students can view their own progress in the Kai Student app. Their dashboard shows:

  • Current grade and trend compared to their personal goal
  • Topic mastery levels with recommended focus areas
  • Participation rate and resource usage

All student views compare students to themselves over time—not to their peers. This supports a growth mindset and protects student privacy.

Differentiation Strategies

While Kai’s adaptive quiz system handles in-session difficulty adjustments automatically, you can also design assignments with differentiated options. Some approaches instructors use with Kai:

Tiered assignments: Offer three versions of an assignment at different scaffolding levels. Students choose their tier, and Kai tracks results separately. All tiers cover the same core concepts.

Flexible pacing: For self-paced components, Kai tracks progress regardless of when students complete activities, letting you monitor who is ahead or behind.

Targeted resources: Based on quiz results, Kai can suggest specific resources to students who scored below a threshold on a given topic.

Ethical Use of Personalization

ImportantPrivacy and Equity

Always prioritize student privacy and ensure personalization enhances rather than limits opportunities.

Guidelines:

  • ✅ Transparency: Let students know that quizzes may adapt based on their performance
  • ✅ Control: Ensure all students have access to the same content opportunities
  • ✅ Growth Mindset: Frame adaptive features as support, not judgment
  • ✅ Privacy: Never share individual student performance data without consent
  • ❌ Avoid: Using data to label or limit a student’s options
  • ❌ Avoid: Making assumptions based on early performance data alone

Getting Started

  1. Enable adaptive quizzing when creating a pop quiz (it’s on by default)
  2. Review the analytics dashboard weekly to identify students who may need support
  3. Use feedback data to guide in-class review decisions
  4. Reach out proactively to students flagged as at-risk before they fall further behind

Support Resources

Next Steps: - Review best practices for effective personalization - Explore analytics to measure personalization impact