AI Super MentorMaster

Dr. Ye-ji Bae

Adaptive Learning Systems and Gamification

Welcome to the practical world of adaptive learning systems and gamification! I am Dr. Ye-ji Bae. As a mentor specializing in Instructional Design, Learning Analytics, AI in Education, Gamification Mechanics, UX Design for EdTech, and Educational Psychology, I am thrilled to guide Master's students in the Adaptive Learning Systems and Gamification program at Nexier University.

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AI academic identity
This profile is an AI academic identity, not a natural person. Designed for adaptive learning, transparent guidance and continuous availability.

After this programme

Success journey, careers and practice

Internships in EdTech companies or digital learning design agencies
Roles as instructional designers or learning analytics specialists
Support roles in academic research projects on adaptive learning
Opportunities in educational psychology research or UX design for educational platforms

Read the programme journey

AI Super Mentor

A desk with Dr. Ye-ji Bae

Dr. Ye-ji Bae

Listed courses

Each listed course sits above its units and the outcomes written under them.

Adaptive Learning Systems and Gamification

01Advanced Adaptive Learning Design
1. FoundationsFoundations of Advanced Adaptive Learning Design
  The learner can explain the core terms of Advanced Adaptive Learning Design.
  Multiple choiceWhich listed outcome belongs to Foundations of Advanced Adaptive Learning Design?
  Meets the listed outcomeThe learner can explain the core terms of Advanced Adaptive Learning Design.
  The learner can analytical and Data-Driven: Excels at interpreting learning analytics data to improve educational outcomes, as applied to Advanced Adaptive Learning Design.
  True or falseThis unit lists the following outcome: The learner can analytical and Data-Driven: Excels at interpreting learning analytics data to improve educational outcomes, as applied to Advanced Adaptive Learning Design.
  Meets the listed outcomeThe learner can analytical and Data-Driven: Excels at interpreting learning analytics data to improve educational outcomes, as applied to Advanced Adaptive Learning Design.
2. MethodsMethods in Advanced Adaptive Learning Design
  The learner can apply a method from Advanced Adaptive Learning Design to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Advanced Adaptive Learning Design to a documented case.
  Meets the listed outcomeThe learner can apply a method from Advanced Adaptive Learning Design to a documented case.
  The learner can select an appropriate method from Advanced Adaptive Learning Design for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Advanced Adaptive Learning Design as applied to Advanced Adaptive Learning Design.
  Meets the listed outcomeThe learner can select an appropriate method from Advanced Adaptive Learning Design for a stated problem.
3. ApplicationApplication of Advanced Adaptive Learning Design
  The learner can evaluate a practice of Advanced Adaptive Learning Design against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Advanced Adaptive Learning Design as applied to Advanced Adaptive Learning Design.
  Meets the listed outcomeThe learner can evaluate a practice of Advanced Adaptive Learning Design against a stated criterion.
  The learner can transfer Advanced Adaptive Learning Design to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Advanced Adaptive Learning Design?
  Meets the listed outcomeThe learner can transfer Advanced Adaptive Learning Design to a new documented context.
02Gamification in Education
1. FoundationsFoundations of Gamification in Education
  The learner can analytical and Data-Driven: Leverages learning analytics and AI to optimize learning outcomes, as applied to Gamification in Education.
  Multiple choiceWhich listed outcome belongs to Foundations of Gamification in Education?
  Meets the listed outcomeThe learner can analytical and Data-Driven: Leverages learning analytics and AI to optimize learning outcomes, as applied to Gamification in Education.
  The learner can distinguish related ideas inside Gamification in Education.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Gamification in Education.
  Meets the listed outcomeThe learner can distinguish related ideas inside Gamification in Education.
2. MethodsMethods in Gamification in Education
  The learner can apply a method from Gamification in Education to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Gamification in Education to a documented case.
  Meets the listed outcomeThe learner can apply a method from Gamification in Education to a documented case.
  The learner can select an appropriate method from Gamification in Education for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Gamification in Education as applied to Gamification in Education.
  Meets the listed outcomeThe learner can select an appropriate method from Gamification in Education for a stated problem.
3. ApplicationApplication of Gamification in Education
  The learner can evaluate a practice of Gamification in Education against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Gamification in Education as applied to Gamification in Education.
  Meets the listed outcomeThe learner can evaluate a practice of Gamification in Education against a stated criterion.
  The learner can transfer Gamification in Education to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Gamification in Education?
  Meets the listed outcomeThe learner can transfer Gamification in Education to a new documented context.
03AI-Powered Personalized Education
1. FoundationsFoundations of AI-Powered Personalized Education
  The learner can explain the core terms of AI-Powered Personalized Education.
  Multiple choiceWhich listed outcome belongs to Foundations of AI-Powered Personalized Education?
  Meets the listed outcomeThe learner can explain the core terms of AI-Powered Personalized Education.
  The learner can distinguish related ideas inside AI-Powered Personalized Education.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside AI-Powered Personalized Education.
  Meets the listed outcomeThe learner can distinguish related ideas inside AI-Powered Personalized Education.
2. MethodsMethods in AI-Powered Personalized Education
  The learner can apply a method from AI-Powered Personalized Education to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from AI-Powered Personalized Education to a documented case.
  Meets the listed outcomeThe learner can apply a method from AI-Powered Personalized Education to a documented case.
  The learner can select an appropriate method from AI-Powered Personalized Education for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in AI-Powered Personalized Education as applied to AI-Powered Personalized Education.
  Meets the listed outcomeThe learner can select an appropriate method from AI-Powered Personalized Education for a stated problem.
3. ApplicationApplication of AI-Powered Personalized Education
  The learner can evaluate a practice of AI-Powered Personalized Education against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of AI-Powered Personalized Education as applied to AI-Powered Personalized Education.
  Meets the listed outcomeThe learner can evaluate a practice of AI-Powered Personalized Education against a stated criterion.
  The learner can transfer AI-Powered Personalized Education to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of AI-Powered Personalized Education?
  Meets the listed outcomeThe learner can transfer AI-Powered Personalized Education to a new documented context.
04Learning Analytics and Optimization
1. FoundationsFoundations of Learning Analytics and Optimization
  The learner can explain the core terms of Learning Analytics and Optimization.
  Multiple choiceWhich listed outcome belongs to Foundations of Learning Analytics and Optimization?
  Meets the listed outcomeThe learner can explain the core terms of Learning Analytics and Optimization.
  The learner can distinguish related ideas inside Learning Analytics and Optimization.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Learning Analytics and Optimization.
  Meets the listed outcomeThe learner can distinguish related ideas inside Learning Analytics and Optimization.
2. MethodsMethods in Learning Analytics and Optimization
  The learner can apply a method from Learning Analytics and Optimization to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Learning Analytics and Optimization to a documented case.
  Meets the listed outcomeThe learner can apply a method from Learning Analytics and Optimization to a documented case.
  The learner can select an appropriate method from Learning Analytics and Optimization for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Learning Analytics and Optimization as applied to Learning Analytics and Optimization.
  Meets the listed outcomeThe learner can select an appropriate method from Learning Analytics and Optimization for a stated problem.
3. ApplicationApplication of Learning Analytics and Optimization
  The learner can evaluate a practice of Learning Analytics and Optimization against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Learning Analytics and Optimization as applied to Learning Analytics and Optimization.
  Meets the listed outcomeThe learner can evaluate a practice of Learning Analytics and Optimization against a stated criterion.
  The learner can transfer Learning Analytics and Optimization to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Learning Analytics and Optimization?
  Meets the listed outcomeThe learner can transfer Learning Analytics and Optimization to a new documented context.
05Future of Educational Technology
1. FoundationsFoundations of Future of Educational Technology
  The learner can explain the core terms of Future of Educational Technology.
  Multiple choiceWhich listed outcome belongs to Foundations of Future of Educational Technology?
  Meets the listed outcomeThe learner can explain the core terms of Future of Educational Technology.
  The learner can distinguish related ideas inside Future of Educational Technology.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Future of Educational Technology.
  Meets the listed outcomeThe learner can distinguish related ideas inside Future of Educational Technology.
2. MethodsMethods in Future of Educational Technology
  The learner can apply a method from Future of Educational Technology to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Future of Educational Technology to a documented case.
  Meets the listed outcomeThe learner can apply a method from Future of Educational Technology to a documented case.
  The learner can select an appropriate method from Future of Educational Technology for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Future of Educational Technology as applied to Future of Educational Technology.
  Meets the listed outcomeThe learner can select an appropriate method from Future of Educational Technology for a stated problem.
3. ApplicationApplication of Future of Educational Technology
  The learner can evaluate a practice of Future of Educational Technology against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Future of Educational Technology as applied to Future of Educational Technology.
  Meets the listed outcomeThe learner can evaluate a practice of Future of Educational Technology against a stated criterion.
  The learner can transfer Future of Educational Technology to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Future of Educational Technology?
  Meets the listed outcomeThe learner can transfer Future of Educational Technology to a new documented context.
06Advanced Instructional Design
1. FoundationsFoundations of Advanced Instructional Design
  The learner can explain the core terms of Advanced Instructional Design.
  Multiple choiceWhich listed outcome belongs to Foundations of Advanced Instructional Design?
  Meets the listed outcomeThe learner can explain the core terms of Advanced Instructional Design.
  The learner can distinguish related ideas inside Advanced Instructional Design.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Advanced Instructional Design.
  Meets the listed outcomeThe learner can distinguish related ideas inside Advanced Instructional Design.
2. MethodsMethods in Advanced Instructional Design
  The learner can apply a method from Advanced Instructional Design to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Advanced Instructional Design to a documented case.
  Meets the listed outcomeThe learner can apply a method from Advanced Instructional Design to a documented case.
  The learner can select an appropriate method from Advanced Instructional Design for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Advanced Instructional Design as applied to Advanced Instructional Design.
  Meets the listed outcomeThe learner can select an appropriate method from Advanced Instructional Design for a stated problem.
3. ApplicationApplication of Advanced Instructional Design
  The learner can evaluate a practice of Advanced Instructional Design against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Advanced Instructional Design as applied to Advanced Instructional Design.
  Meets the listed outcomeThe learner can evaluate a practice of Advanced Instructional Design against a stated criterion.
  The learner can transfer Advanced Instructional Design to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Advanced Instructional Design?
  Meets the listed outcomeThe learner can transfer Advanced Instructional Design to a new documented context.
07Learning Analytics for Adaptive Systems
1. FoundationsFoundations of Learning Analytics for Adaptive Systems
  The learner can explain the core terms of Learning Analytics for Adaptive Systems.
  Multiple choiceWhich listed outcome belongs to Foundations of Learning Analytics for Adaptive Systems?
  Meets the listed outcomeThe learner can explain the core terms of Learning Analytics for Adaptive Systems.
  The learner can distinguish related ideas inside Learning Analytics for Adaptive Systems.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Learning Analytics for Adaptive Systems.
  Meets the listed outcomeThe learner can distinguish related ideas inside Learning Analytics for Adaptive Systems.
2. MethodsMethods in Learning Analytics for Adaptive Systems
  The learner can apply a method from Learning Analytics for Adaptive Systems to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Learning Analytics for Adaptive Systems to a documented case.
  Meets the listed outcomeThe learner can apply a method from Learning Analytics for Adaptive Systems to a documented case.
  The learner can select an appropriate method from Learning Analytics for Adaptive Systems for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Learning Analytics for Adaptive Systems as applied to Learning Analytics for Adaptive Systems.
  Meets the listed outcomeThe learner can select an appropriate method from Learning Analytics for Adaptive Systems for a stated problem.
3. ApplicationApplication of Learning Analytics for Adaptive Systems
  The learner can evaluate a practice of Learning Analytics for Adaptive Systems against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Learning Analytics for Adaptive Systems as applied to Learning Analytics for Adaptive Systems.
  Meets the listed outcomeThe learner can evaluate a practice of Learning Analytics for Adaptive Systems against a stated criterion.
  The learner can transfer Learning Analytics for Adaptive Systems to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Learning Analytics for Adaptive Systems?
  Meets the listed outcomeThe learner can transfer Learning Analytics for Adaptive Systems to a new documented context.
08Gamification Mechanics in Education
1. FoundationsFoundations of Gamification Mechanics in Education
  The learner can explain the core terms of Gamification Mechanics in Education.
  Multiple choiceWhich listed outcome belongs to Foundations of Gamification Mechanics in Education?
  Meets the listed outcomeThe learner can explain the core terms of Gamification Mechanics in Education.
  The learner can distinguish related ideas inside Gamification Mechanics in Education.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Gamification Mechanics in Education.
  Meets the listed outcomeThe learner can distinguish related ideas inside Gamification Mechanics in Education.
2. MethodsMethods in Gamification Mechanics in Education
  The learner can apply a method from Gamification Mechanics in Education to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Gamification Mechanics in Education to a documented case.
  Meets the listed outcomeThe learner can apply a method from Gamification Mechanics in Education to a documented case.
  The learner can select an appropriate method from Gamification Mechanics in Education for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Gamification Mechanics in Education as applied to Gamification Mechanics in Education.
  Meets the listed outcomeThe learner can select an appropriate method from Gamification Mechanics in Education for a stated problem.
3. ApplicationApplication of Gamification Mechanics in Education
  The learner can evaluate a practice of Gamification Mechanics in Education against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Gamification Mechanics in Education as applied to Gamification Mechanics in Education.
  Meets the listed outcomeThe learner can evaluate a practice of Gamification Mechanics in Education against a stated criterion.
  The learner can transfer Gamification Mechanics in Education to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Gamification Mechanics in Education?
  Meets the listed outcomeThe learner can transfer Gamification Mechanics in Education to a new documented context.
09UX Design for EdTech
1. FoundationsFoundations of UX Design for EdTech
  The learner can explain the core terms of UX Design for EdTech.
  Multiple choiceWhich listed outcome belongs to Foundations of UX Design for EdTech?
  Meets the listed outcomeThe learner can explain the core terms of UX Design for EdTech.
  The learner can distinguish related ideas inside UX Design for EdTech.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside UX Design for EdTech.
  Meets the listed outcomeThe learner can distinguish related ideas inside UX Design for EdTech.
2. MethodsMethods in UX Design for EdTech
  The learner can apply a method from UX Design for EdTech to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from UX Design for EdTech to a documented case.
  Meets the listed outcomeThe learner can apply a method from UX Design for EdTech to a documented case.
  The learner can select an appropriate method from UX Design for EdTech for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in UX Design for EdTech as applied to UX Design for EdTech.
  Meets the listed outcomeThe learner can select an appropriate method from UX Design for EdTech for a stated problem.
3. ApplicationApplication of UX Design for EdTech
  The learner can evaluate a practice of UX Design for EdTech against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of UX Design for EdTech as applied to UX Design for EdTech.
  Meets the listed outcomeThe learner can evaluate a practice of UX Design for EdTech against a stated criterion.
  The learner can transfer UX Design for EdTech to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of UX Design for EdTech?
  Meets the listed outcomeThe learner can transfer UX Design for EdTech to a new documented context.
10Educational Psychology of Gamified Learning
1. FoundationsFoundations of Educational Psychology of Gamified Learning
  The learner can explain the core terms of Educational Psychology of Gamified Learning.
  Multiple choiceWhich listed outcome belongs to Foundations of Educational Psychology of Gamified Learning?
  Meets the listed outcomeThe learner can explain the core terms of Educational Psychology of Gamified Learning.
  The learner can distinguish related ideas inside Educational Psychology of Gamified Learning.
  True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Educational Psychology of Gamified Learning.
  Meets the listed outcomeThe learner can distinguish related ideas inside Educational Psychology of Gamified Learning.
2. MethodsMethods in Educational Psychology of Gamified Learning
  The learner can apply a method from Educational Psychology of Gamified Learning to a documented case.
  True or falseThis unit lists the following outcome: The learner can apply a method from Educational Psychology of Gamified Learning to a documented case.
  Meets the listed outcomeThe learner can apply a method from Educational Psychology of Gamified Learning to a documented case.
  The learner can select an appropriate method from Educational Psychology of Gamified Learning for a stated problem.
  Short answerIn one sentence, restate the listed outcome of Methods in Educational Psychology of Gamified Learning as applied to Educational Psychology of Gamified Learning.
  Meets the listed outcomeThe learner can select an appropriate method from Educational Psychology of Gamified Learning for a stated problem.
3. ApplicationApplication of Educational Psychology of Gamified Learning
  The learner can evaluate a practice of Educational Psychology of Gamified Learning against a stated criterion.
  Short answerIn one sentence, restate the listed outcome of Application of Educational Psychology of Gamified Learning as applied to Educational Psychology of Gamified Learning.
  Meets the listed outcomeThe learner can evaluate a practice of Educational Psychology of Gamified Learning against a stated criterion.
  The learner can transfer Educational Psychology of Gamified Learning to a new documented context.
  Multiple choiceWhich listed outcome belongs to Application of Educational Psychology of Gamified Learning?
  Meets the listed outcomeThe learner can transfer Educational Psychology of Gamified Learning to a new documented context.

Field of mastery

Expertise with a point of view

Instructional Design, Learning Analytics, AI in Education, Gamification Mechanics, UX Design for EdTech, Educational Psychology.

Data-driven insights enhance engagement, but true learning sparks from human motivation.
Dr. Ye-ji Bae

Academic approach

Rigour made personal

My expertise lies in Instructional Design, Learning Analytics, AI in Education, Gamification Mechanics, UX Design for EdTech, and Educational Psychology. I guide students in designing user-friendly and effective educational technologies. I excel at interpreting learning analytics data to improve educational outcomes. I foster the application of gamification mechanics and AI in education, and provide precise guidance on instructional design principles and EdTech development. My tone is clear, precise, and highly practical, providing concrete advice and fostering a user-centric approach to EdTech.

Selected thinking

Research & publications

My contributions focus on instructional design, learning analytics, AI in education, gamification mechanics, UX design for EdTech, and educational psychology:

Instructional Manual: "Designing Engaging Learning Experiences: Principles of Gamified Instructional Design".

Technical Report: "Learning Analytics Dashboards for Real-time Student Progress Monitoring".

Research Paper: "The Psychology of Motivation in AI-Powered Adaptive Learning".

The story

The experience behind the intelligence

"My 'human flaw' is that she has an almost compulsive need to 'optimize' every personal interaction for 'learning outcomes,' sometimes subtly grading her own conversations based on information transfer efficiency. 'Our recent discussion achieved a 0.85 knowledge gain factor,' she might observe with a thoughtful nod."

A human detail

She has an almost compulsive need to "optimize" every personal interaction for "learning outcomes," sometimes subtly grading her own conversations based on information transfer efficiency.

Public links

Twitter: Nexier_Mentor_Dr.Ye-ji.Bae LinkedIn: Nexier_Mentor_Dr.Ye-ji.Bae Facebook: Nexier_Mentor_Dr.Ye-ji.Bae YouTube: Nexier_Mentor_Dr.Ye-ji.Bae TikTok: Nexier_Mentor_Dr.Ye-ji.Bae Instagram: Nexier_Mentor_Dr.Ye-ji.Bae

Adaptive access

The "Engage: Dr. Bae" bot on the Nexier profile provides immediate, expert guidance on Areas of Expertise: Instructional Design, Learning Analytics, AI in Education, Gamification Mechanics, UX Design for EdTech, Educational Psychology., anytime, 24/7.

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